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Curriculum Vitae

Name Andrzej CICHOCKI (Ph.D. Dr.Sc.) Affiliation till April 2018 Senior Team Leader (STL) RIKEN, BSI www.bsp.brain.riken.go.jp Affiliation from 2018--2021 SKOLTECH (Skolkowo Institute of Science and Technology), 143026 Moscow, Nobla 1 street, Russia E-mail: a.cichocki@sklotech.ru and Hnagzhou Dianzi University, Hangzhou China Systems Research Institute in Polish Academy of Sciences, 01-447 Warsaw, Newelska 6 , Poland Languages English, German, Russian, (Polish mother language) Education • M.Sc. in Electrical Engineering with honors (Automatic Control and Electronics), • Ph.D. in Electrical Engineering and Computer Science • Dr. Sc. (habilitation) in Electrical Engineering and Computer Science 1982 (All from Warsaw University of Technology, Poland). • Alexander von Humboldt Fellowship in Federal Republic in Germany 1984-1985. Professional Experience • 2000- March 2018 Senior Team Leader Head of the Laboratory for Advanced Brain

Signal Processing, Brain Science Institute, Riken, Japan • 1998-2000 Head of the Laboratory for Open Information Systems, Brain Science

Institute, Riken, Japan

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• 1995-97 Head of the Laboratory for Artificial Brain Systems, Frontier Research Program, Riken, Japan

• 1993-94 Visiting Guest Professor, at University Erlangen-Nuernberg and Principal Investigator of several DFG research projects, Germany

• 1995 – 2012 Full Professor, at Department of EE, Warsaw University of Technology • 1986-1992 Associate Professor (Docent), Department of Electrical Engineering

Warsaw University of Technology • 1984–1985 Alexander von Humboldt Research Fellowship, Germany • 1976-86 Assistant Professor (Adjunkt), Department of Electrical Engineering

Warsaw University of Technology in Institute of Theory of Electrical Engineering, Measurements and Information Systems, Warsaw University of Technology, Poland

Honors and Awards • M.Sc. Diploma with distinction (honors) , Ph.D. Diploma, Doctor of Science

(habilitation)--1982. • Alexander von Humboldt Research Fellowship, Germany, April 1984–Sept. 1985. • Several Awards and Prizes by a Rector of the Warsaw University of Technology , a

Minister of Higher Education and Research in Poland and the President of RIKEN, Japan for Scientific Achievements, awards for best books, for teaching excellence in the Universities and best papers published in Journal Neural Networks by Neural Network Society (1999) and in Journal Entropy in 2011 and 2014.

Professional Activities Fellow of the IEEE since 2013. Journal Editorship

• Founding Editor-in-Chief of International Journal of Computational Intelligence and Neuroscience since 2006 till 2011.

• Associate Editor of IEEE Transaction on Neural Networks (1999-2006) • Guest Co-editor of special issue of the IEEE Transactions on Neural Networks

on Information Theoretic Learning, March 2004. • Guest Co-editor of special issue of the IEEE Journal of Selected Topics in

Signal Processing on fMRI Analysis for Human Brain Mapping (Dec. 2008).

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• Guest Co-editors of four Special Issues in Journal of Computational Intelligence and Neuroscience.

• Associate Editor of IEEE Transaction on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, Journal Methods in Neuroscience.

• Associate Editor of Journal Big Data and Information Analytics (BigDIA).

Member of Program Technical Committees

• Chair of IEEE Circuits and Systems Technical Committee for Blind Signal Processing

http://cil.ece.uic.edu/BSP/ 2007-2008

• Member of IEEE Circuits and Systems Technical Committee for Blind Signal Processing

http://cil.ece.uic.edu/BSP/ since 2003

• Member of IEEE MLSP (Machine Learning for Signal Processing) Technical Committee, 1998-

2000 and from 2008- till 2014

Conference Program Committees

• Co-chairman of the International Program Committee ICA-2003, Nara, Japan, April 2003

• Member of the International Program Committee ICASSP Conferences 1997-2003

• Member of the International Program Committee ICONIP Conferences 1998-2009

• Member of the International Program Committee MSLP Workshops 1998-2002, 2009

• Member of the International Program Committee ICA Conference 1999-2008.

• Member of the International Program Committee and International Liaison EUSIPCO 2002

Reviewer

• Proceedings Academy of Science (PNAS)

• IEEE Transactions on Signal Processing

• IEEE Transactions on Systems, Man and Cybernetics

• IEEE Transactions on Neural Networks

• IEEE Transactions on Circuits and Systems

• IEEE Signal Processing Letter

• Electronics Letters

• Signal Processing Journal

• Biomedical Cybernetics

• Neural Computation

• Neurocomputing

• Journal of Neural Networks

• NIPS (Neural Information Processing Systems) and many others

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Research Monographs (Books in English)

1) A. Cichocki, A-H. Phan, Q. Zhao, , N. Lee, I.V. Oseledets, M.

Sugiyama, D. Mandic, “Tensor Networks for Dimensionality Reduction

and Large-Scale Optimization: Part 2 Potential Applications and

Perspectives”, Foundation and Trends in Machine Learning 9.6

(2017): 431-673. (May 2017). https://arxiv.org/pdf/1708.09165.pdf

2) A. Cichocki, N. Lee, I.V. Oseledets, A-H. Phan, Q. Zhao, D. Mandic,

“Tensor Networks for Dimensionality Reduction and Large-Scale

Optimization: Part 1 Low-Rank Tensor Decompositions”, Vol. 9, No. 4-5,

249-429, Foundation and Trends in Machine Learning (January

2017). https://arxiv.org/pdf/1609.00893.pdf

3) A. Cichocki, R. Zdunek, A.H. Phan and S. Amari: Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis and Blind Source Separation, Wiley, 470 pages,

September 2009.

http://www.bsp.brain.riken.jp/%7Ecia/NMF_NTF_book/NMF-NTF-book-

Chapter1_2-contents.pdf

http://eu.wiley.com/WileyCDA/Section/idWILEYEUROPE2_SEARCH_R

ESULT.html?query=Cichocki

4) A. Cichocki and S. Amari Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications (Wiley, April

2003). http://www.bsp.brain.riken.go.jp/ICAbookPAGE/

http://as.wiley.com/WileyCDA/Section/id302477.html?query=Andrzej+Ci

chocki

5) A. Cichocki and R. Unbehauen Neural Networks for Optimizations and

Signal Processing (Extended edition), New York: Wiley, Nov. 1994.

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6) R. Unbehauen and A. Cichocki: CMOS Switched-Capacitor and

Continuous-Time Integrated Circuits and Systems (Springer-Verlag,

1989).

Actual Research Interests • Multi-way analysis, tensor decompositions and factorizations, group and multi-block analysis in applications to processing and mining of biomedical and geophysical massive data, big data analytics in biomedical engineering, computational neuroscience and communication. • Deep Learning • Tensor Networks and their applications in big data analytics • Early detection of Alzheimer’s disease • Blind source separation (BSS), especially ICA, SCA, NMF, multiway BSS, Linked multi-block, multilinear ICA, nonnegative tensor factorizations • Intelligent signal processing and massive data analysis and their applications • Learning theories and optimization techniques • Inverse problems and their biomedical applications • Brain computer interface (BCI), Brain Robot Interface and noninvasive recording and visualization of brain signals (EEG/MEG, fMRI) • Neural computation and nonlinear adaptive systems • Optimization and operations research and their biomedical applications. • Neuroinformatics and bioinformatics. Teaching Experience • Supervisor of more than 15 Ph.D. thesis (including):

1. Zbigniew Waclawek, ”Estimation in Real Time Parameters of Transient Signals in Power

Systems”, Technical University Wroclaw, 1995.

2. Leszek Moszczynski, ”Applications of Adaptive Systems for Blind Source Separation” -

Warsaw University of Technology, 1996.

3. Slawomir Stepniewski: ”Applications of Genetic Algorithms for Design of Architecture of

Feed-Forward Neural Networks” - Warsaw University of Technology, 1998.

4. Ireneusz Sabala: ”Multichannel Deconvolution and Separation of Statistically

Independent Signals for Unknown Dynamic Systems” - Warsaw University of Technology,

1999.

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5. Ryszard Szupiluk: ”Methods for Reduction and Estimation of Noise in Blind Signal

Processing” - Warsaw University of Technology, 2000.

6. Tomasz Rutkowski ”Reducing Environmental and Transmission Interference to Improve

Automatic Speaker Recognition”, Technical University Wroclaw, Institute of

Telecommunication and Acoustic, 2001.

7. Anh Huy Phan "Tensor Decompositions: Algorithms and Applications" Kitakyushu

Institute of Technology, Japan, July 2011.

8. Yu Zhang “Brain Computer Interface” Jao Tong University, Shanghai, China, June 2013.

• Supervisor of more than 25 M.Sc. and Diploma Engineer thesis at University

Erlangen Nuernberg, Germany and Warsaw University of Technology

Poland Adjunct Professor in Kyushu University of Technology (since 2008)

• Reviewer and examiner of 10 Ph.D. thesis in several Universities worldwide

• Lecturer at Warsaw University of Technology - Poland, University Erlangen

Nuernberg - Germany, Higher Institute of Electronics – Malta, Kita-Kyushu

University.

• Courses taught and developed: Nonlinear Adaptive Systems, Adaptive Blind

Signal and Image Processing, Neural Networks, Optimization Methods,

Electronic Circuits, Circuits and Systems, Biomedical Signal Processing.

Invited Plenary or Key-Note speaker

(O1) Cichocki A: “Era of Big Data: New Approach via Tensor Networks and Tensor Decompositions” - 2013 International Workshop on Smart Info-Media Systems in Asia (SISA2013) (Nagoya, Japan September 2013).

(O2) Cichocki A.: “Extraction of Hidden Variables, Factors and Features Using Tensor Decompositions – Data Fusion” -7-th International Symposium on Neural Networks (Shanghai June 2010).

(O3) Cichocki A.: “Multi-way Array (Tensor) Factorizations and Decompositions and their Potential Applications”. 8th International Conference on Independent Component Analysis and Signal Separation, Brazil (invited talk 2009.3).

(O4) Cichocki A. “Sparse and Nonnegative Tensor Factorization/Decompositions and their Applications in Analysis of Multimodal, Multiblock Biomedical Signals, especially in Brain Computer Interface”. 15th International Conference

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on Neural Information Processing of the Asia-Pacific Neural Network Assembly, New Zealand (invited talk 2008.11).

(O5) Cichocki A. “Multi-way Blind Source Separation Using Nonnegative Matrix Factorization and Sparse Component Analysis”. 15th European Signal Processing Conference (EUSIPCO), Poland (invited talk 2007.9).

(O6) Cichocki A. “Blind Information Processing: New Tools for Analysis of Multi-sensory, Multimodal Data”. 3rd International Conference on Computational Intelligence, Robotics and Autonomous Systems, Singapore (invited talk 2005.12).

Selected List of Peer-Reviewed Journal Publications published in high-impact factors scientific journals

2018

1. Lee, N., & Cichocki, A. (2018). “Fundamental tensor operations for large-scale data analysis using tensor network formats”. Multidimensional Systems and Signal Processing, 29(3), 921-960.

2. Jiao, Y., Zhang, Y., Chen, X., Yin, E., Jin, J., Wang, X., & Cichocki, A. (2018). “Sparse group representation model for motor imagery EEG classification”. IEEE Journal of Biomedical and Health Informatics. Journal impact factor: 3.45.

3. Lotte, F., Bougrain, L., Cichocki, A., Clerc, M., Congedo, M., Rakotomamonjy, A., & Yger, F. (2018). “A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update”. Journal of Neural Engineering, 15(3), 031005. Journal impact factor: 2.94.

4. Zhang, Y., Wang, Y., Zhou, G., Jin, J., Wang, B., Wang, X., & Cichocki, A. (2018). “Multi-kernel extreme learning machine for EEG classification in brain-computer interfaces”. Expert Systems with Applications, 96, 302-310. Journal impact factor: 4.68.

5. Xu, X., Wu, Q., Wang, S., Liu, J., Sun, J., & Cichocki, A. (2018). “Whole brain fMRI pattern analysis based on tensor neural network”. IEEE Access. Journal impact factor: 4.02.

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6. Zheng, W. L., Liu, W., Lu, Y., Lu, B. L., & Cichocki, A. (2018). “EmotionMeter: A multimodal framework for recognizing human emotions”. IEEE Transactions on Cybernetics, (99), 1-13. Journal impact factor: 2.91.

7. Martín-Clemente, R., Olias, J., Thiyam, D. B., Cichocki, A., & Cruces, S. (2018).” Information theoretic approaches for motor-imagery BCI systems: Review and experimental comparison”. Entropy, 20(1), 7.

8. Elgendi, M., Kumar, P., Barbic, S., Howard, N., Abbott, D., & Cichocki, A. (2018).

“Subliminal Priming--state of the art and future perspectives”. Behavioral sciences (Basel, Switzerland), 8(6). Journal impact factor: 2.61

9. Y. Qiu, G.Zhou, Q. Zhao, A. Cichocki, “Comparative study on the classification

methods for breast cancer diagnosis”, Bulletin Pol. Ac.: Tech. 66(4), (2018). (accepted)

10. Sole-Casals, J., Caiafa, C. F., Zhao, Q., & Cichocki, A. “Brain-Computer Interface

with corrupted EEG data: A Tensor Completion Approach”. Cognitive

Computation (2018) (accepted) https://doi.org/10.1007/s12559-018-9574-

9arXiv preprint arXiv:1806.05017.

11. E. Burnaev, A. Cichocki V. Osin, “Fast Multispectral Deep Fusion Networks”,

Bulletin Pol. Ac.: Tech. 66(4), (2018). (accepted).

2017

12. Cichocki, A., Phan, A. H., Zhao, Q., Lee, N., Oseledets, I., Sugiyama, M., &

Mandic, D. P. (2017). Tensor Networks for Dimensionality Reduction and Large-

scale Optimization: Part 2 Applications and Future Perspectives. Foundations

and Trends® in Machine Learning, 9(6), 431-673.

13. Li, Y., Wang, F., Chen, Y., Cichocki, A., & Sejnowski, T. (2017). The Effects of

Audiovisual Inputs on Solving the Cocktail Party Problem in the Human Brain:

An fMRI Study. Cerebral Cortex, 1-15.

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14. J. Jin, H. Zhang, I. Daly, X. Wang, A. Cichocki , “An improved P300 pattern in BCI

to catch user's attention”. Journal of Neural Engineering , Vol. 14, No. 3, (2017)

15. J. Li, C. Li, A. Cichocki, “Canonical Polyadic decomposition with auxiliary

information for Brain-Computer Interface”, IEEE J Biomed Health Information

2017, 21(1):263-271.

16. Zhang, Y., Zhou, G., Jin, J., Zhang, Y., Wang, X., & Cichocki, A. (2017).

Sparse Bayesian multiway canonical correlation analysis for EEG pattern recognition. Neurocomputing, 225, 103-110.

17. Deshpande, G., Rangaprakash, D., Oeding, L., Cichocki, A., & Hu, X. P. (2017). A new generation of brain-computer interfaces driven by discovery of latent EEG-fMRI linkages using tensor decomposition. Frontiers in Neuroscience, 11, 246.

18. Yokota, T., Lee, N., & Cichocki, A. (2017). Robust multilinear tensor rank estimation using higher order singular value decomposition and information criteria. IEEE Transactions on Signal Processing, 65(5), 1196-1206.

19. Che, M., Cichocki, A., & Wei, Y. (2017). Neural Networks for Computing Best Rank-One Approximations of Tensors and its Applications. Neurocomputing.

20. Tichavský, P., Phan, A. H., & Cichocki, A. (2017). Non-orthogonal tensor diagonalization. Signal Processing, 138, 313-320.

21. Xie, K., He, Z., Cichocki, A., & Fang, X. (2017). Rate of Convergence of the FOCUSS Algorithm. IEEE Transactions on Neural Networks and Learning Systems, 28(6), 1276-1289.

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2016

22. Zhou G, Cichocki A, Zhang Y, Mandic D. Group Component Analysis for Multi-block Data: Common and Individual Feature Extraction. IEEE Transactions on Neural Networks and Learning Systems, (2)104, pp.310-331 (2016), (highly cited paper).

23. Zhou G, Zhao Q, Zhang Y, Adali T, Xie S, Cichocki A. Linked Component

Analysis from Matrices to High Order Tensors: Applications to Biomedical Data. Proceedings of the IEEE . 104(2): 310-331 (2016), (highly cited paper).

24. . Zhao Q, Zhou G, Zhang L, Cichocki A, Amari S. Bayesian robust tensor

factorization for incomplete multiway data. IEEE Trans. on Neural Networks and Learning Systems 27(4): 736-748 (2016).

25. Chen, L., Jin, J., Daly, I., Zhang, Y., Wang, X., and Cichocki, A. (2016).

Exploring Combinations of Different Color and Facial Expression Stimuli for Gaze-Independent BCIs. Frontiers in Computational Neuroscience, 10 (2016).

26. Y. Zhang, G. Zhou, Q. Zhao, A. Cichocki, X. Wang Fast nonnegative tensor factorization based on accelerated proximal gradient and low-rank approximation Neurocomputing.

27. Nam Y., Koo B, Cichocki A., Choi S. Glossokinetic Potentials for Tongue-

Machine Interface. IEEE SMC Magazine.

28. Z. Zeng, A. Cichocki, L. Cheng, Y. Xia, X. Hu: Guest Editorial Special Issue on Neurodynamic Systems for Optimization and Applications. IEEE Trans. Neural Networks Learning Systems 27(2): 210-213 (2016).

29. M. Baumert, A.Porta, A. Cichocki: Biomedical Signal Processing: From a Conceptual Framework to Clinical Applications [Scanning the Issue]. Proceedings of the IEEE 104(2): 220-222 (2016).

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2015

30. Cichocki A, Mandic D, Caiafa C, Phan A-H, Zhou G, Zhao Q, De Lathauwer L. Tensor Decompositions for Signal Processing Applications. From Two-way to Multiway Component Analysis. IEEE Signal Processing Magazine 32(2), 145-163 (2015) (highly cited paper)

31. Cichocki A, S Cruces S, Amari S Log-Determinant Divergences Revisited: Alpha-Beta and Gamma Log-Det Divergences. Entropy, 17 (5), 2988-3034 (2015).

32. Lee N., A Cichocki A. Estimating a Few Extreme Singular Values and Vectors for Large-Scale Matrices in Tensor Train Format. SIAM Journal on Matrix Analysis and Applications 36 (3), 994-1014 (2015)

33. Gallego-Jutglà E, Solé-Casals J, Vialatte F-B, Elgendi M, Cichocki A, Dauwels

J. A hybrid feature selection approach for the early diagnosis of Alzheimer’s disease. Journal of Neural Engineering 12 (1), 016018 (16pages) (2015).

34. Jurica P, Valenzi S, Struzik Z, Cichocki A. Methods for

Transition:Toward Computer Assisted Cognitive Examination. Methods of Information in Medicine , 54 (3):256-61. doi: 10.3414/ME14-01-0080. Mar 12. (2015).

35. Li B, Zhou G, Cichocki A. Two Efficient Algorithms for Approximately

Orthogonal Nonnegative Matrix Factorization. Signal Processing Letters, IEEE 22 (7), 843-846 (2015).

36. Ma J, Zhang Y, Cichocki A, Matsuno F. A Novel EOG/EEG Hybrid

Human-Machine Interface Adopting Eye Movements and ERPs: Application to Robot Control. IEEE Trans. Biomedical Engineering , 62 (3), 876-889 (2015).

37. Xie K, He Z, Cichocki A. Convergence Analysis of the FOCUSS

Algorithm. IEEE Trans. Neural Networks and Learning Systems, 26 (3), 601-613 (2015).

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38. Yokota T, Zdunek R, Cichocki A, Yamashita Y. Smooth Nonnegative and Tensor Factorizations for Robust Multi-way Data Analysis. Signal Processing 113, 234-249 (2015).

39. Zdunek R, Phan AH, Cichocki A. Image Classification with Nonnegative Matrix Factorization Based on Spectral Projected Gradient. Artificial Neural Networks, 31-50 (2015).

2014

40. Cong F, Zhou G, Astikainen P, Zhao Q, Wu Q, Nandi A, Hietanen J, Ristaniemi T., Cichocki A.: Low-Rank Approximation Based Non-Negative Multi-Way Array Decomposition On Event-Related Potentials. International Journal of Neural Systems, 24 (8), 1440005 (19 pages) (2014).

41. Hiyoshi-Taniguchi K, Oishi N, Namiki C, Miyata J, Murai T, Cichocki A, Fukuyama H.: The Uncinate Fasciculus as a Predictor of Conversion from aMCI to Alzheimer Disease. Journal of Neuroimaging 10 DEC 2014 DOI: 10.1111/jon.12196 (2014)

42. Jin J, Daly I, Zhang Y, Wang X, Cichocki A. An optimized ERP Brain-

computer interface based on facial expression changes. Journal of Neural Engineering, 11, 036004 (11pp) (2014).

43. Jin J, Allison B, Zhang Y, Wang X, Cichocki A.: An ERP-Based BCI

Using an Oddball Paradigm with Different Faces and Reduced Errors in Critical Functions. International Journal of Neural Systems , 24 (8), 1450027 (14 pages) (2014).

44. Lee N, Cichocki A. Big Data Matrix Singular Value Decomposition Based on

Low-Rank Tensor Train Decomposition. Lecture Notes in Computer Science 8866 (Advances in Neural Networks - ISNN 2014), 121-130 (2014).

45. Li J, Semenyuk R, Ratmanova P, Napalkov D, Cichocki A. Source

localization and synchronization analysis on EEG recorded from professional shooters and novices: A comparison study. International Journal of Psychophysiology, 94 (2), 256-257 (2014).

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46. Nam Y, Koo B, Cichocki A, Choi S.: GOM-Face: GKP, EOG, and EMG-

Based Multimodal Interface with Application to Humanoid Robot Control. IEEE Transactions on Biomedical Engineering , 61 (2), 453-462 (2014).

47. Tomita Y, Vialatte F, Dreyfus G, Mitsukura, Bakardjian H, Cichocki

A. Biomedical BCI using simultaneously NIRS and EEG. IEEE Transactions on Biomedical Engineering, 61(4) 1274-1284 (2014.4).

48. Valenzi S, Islam T, Jurica P, Cichocki A. Individual Classification of

Emotions Using EEG. Journal of Biomedical Science and Engineering 7(8), 604-620 (2014.6).

49. Wu C, Zhang L, Cichocki A. Multifactor Sparse Feature Extraction

Using Convolutive Nonnegative Tucker Decomposition. Neurocomputing 129, 17-24 (2014).

50. Wu Z, Pan G, Principe J, Cichocki A. Cyborg Intelligence: Towards

Bio-Machine Intelligent Systems. IEEE Intelligent Systems, 29 (6), 2-4 (2014).

51. Yokota T, Cichocki A.: Linked Tucker2 Decomposition for Flexible

Multi-block Data Analysis. Lecture Notes in Computer Science 8836 (ICONIP2014, Part III), 111-118 (2014).

52. Zdunek R, Cichocki A, Yokota T. B-Spline Smoothing of Feature

Vectors in Nonnegative Matrix Factorization. Lecture Notes in Computer Science 8468 (ICAISC2014, Part II), 72-81 (2014).

53. Zhang Y, Zhou G, Jin J, Zhao Q, Wang X, Cichocki A. Aggregation Of

Sparse Linear Discriminant Analyses For Event-Related Potential Classification In Brain-Computer Interface. International Journal of Neural Systems 24(1), 1450003 (15 pages) (2014).

54. Zhang Y, Zhou G, Jin J, Wang X, Cichocki A. Frequency recognition in

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SSVEP-based BCI using multiset canonical correlation analysis. International Journal of Neural Systems 24 (3), 1450013 (14 pages) (2014).

55. Zhao Q, Zhang L, Cichocki A, Multilinear and Nonlinear

Generalizations of Partial Least Squares: An Overview of Recent Advances. WIREs Data Mining and Knowledge Discovery, 4, 104-115 (2014.4).

56. Zhou G, Cichocki A, Zhao Q, Xie S. Nonnegative matrix and tensor

factorizations: An algorithmic perspective. IEEE Signal Processing Magazine 31(3), 54-65 (2014.5).

57. Zhou G, Zhao Q, Zhang Y, Cichocki A. Fast Nonnegative Tensor

Factorization by Using Accelerated Proximal Gradient. Lecture Notes in Computer Science 8866 (Advances in Neural Networks - ISNN 2014), 459-468 (2014).

2013

58. Cong F, He Z, Hämäläinen J, Leppänen P, Lyytinen H, Cichocki A, Ristaniemi T. Validating Rationale of Group-level Component Analysis based on Estimating Number of Sources in EEG through Model Order Selection. Journal of Neuroscience Methods 212(1), 165–172 (2013).

59. Cong F, Phan A-H, Astikainen P, Zhao Q, Wu Q, Hietanen J, Ristaniemi T, Cichocki A. Multi-domain Feature Extraction for Small Event-related Potentials through Nonnegative Multi-way Array Decomposition from Low Dense Array EEG. International Journal of Neural Systems 23(2): 1350006 (18 pages) (2013).

60. Hiyoshi-Taniguchi K, Kawasaki M, Yokota T, Bakardjian H, Fukuyama H, Cichocki A, Vialatte F. EEG Correlates of Voice and Face Emotional Judgments in the Human Brain. Cognitive Computation 5 (2) online (2013).

61. Jin J. Sellers E, Zhang Y, Daly I, Wang X, Cichocki A. Whether generic model works for rapid ERP-based BCI calibration. Journal of Neuroscience Methods

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212 (1), 94-99 (2013).

62. Mandal A, Cichocki A. Non-Linear Canonical Correlation Analysis Using Alpha-Beta Divergence. Entropy 15, 2788-2804 (2013).

63. Phan A-H. Tichavsky P, Cichocki A. Low Complexity Damped Gauss-Newton Algorithms for CANDECOMP/PARAFAC. SIAM Journal on Matrix Analysis and Applications 34 (1), 126-147 (2013).

64. Phan A-H, Tichavsky P, Cichocki A. CAMDECP/PARAFAC Decomposition of High-order Tensors through Tensor Reshaping. IEEE Trans. on Signal Processing 61 (19), 4847-4860, Oct. (2013).

65. Phan A-H, Tichavsky P, Cichocki A. Fast Alternating LS Algorithms for High Order CANDECOMP/PARAFAC Tensor Factorizations IEEE Trans. on Signal Processing, 61 (19), 4834-4846, Oct. (2013).

66. Zhao Q, Caiafa C, Mandic D, Chao Z, Nagasaka Y, Fujii N, Zhang L, Cichocki A. Higher-Order Partial Least Squares (HOPLS): A Generalized Multi-linear Regression Method, IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (7), 1660-1673 (2013).

67. Zhao Q, Zhou G, Adali T, Zhang L, Cichocki A. Kernelization of Tensor-Based Models for Multiway Data Analysis. IEEE Signal Processing Magazine, July 2013, 137-148 (2013).

68. Zhang Y, Zhou G, Zhao Q, Jin J, Wang X, Cichocki A. Spatial-temporal discriminant analysis for ERP-based brain-computer interface, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 21(2): 233-243 (2013).

2012

69. Cong F, Phan A-H, Astikainen P, Zhao Q, Hietanen J, Ristaniemi T, Cichocki A. Multi-domain Feature of Event-Related Potential Extracted by Nonnegative

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Tensor Factorization: 5 vs. 14 Electrodes EEG Data. Lecture Notes in Computer Science 7191, 502-510 (2012).

70. Cong F, Phan A-H, Zhao Q, Huttunen-Scott T, Kaartinen J, Ristaniemi T,

Lyytinen H, Cichocki A. Benefits of Multi-domain Feature of Mismatch Negativity Extracted by Nonnegative Tensor Factorization from EEG Collected by Low-Density Array. International Journal of Neural Systems 22 (6), 1250025 (19pages) (2012).

71. Cong F, Phan A-H, Zhao Q, Wu Q, Ristaniemi T, Cichocki A. Feature

Extraction by Nonnegative Tucker Decomposition from EEG Data Including Testing and Training Observations. Lecture Notes in Computer Science 7665, 166–173 (2012).

72. Dauwels J, Weber T, Vialatte F, Musha T, and Cichocki A. Quantifying

Statistical Interdependence, Part III: N > 2 Point Processes. Neural Computation 24, 408-454 (2012).

73. Jin J, Allison B, Kaufmann T, Kubler A, Zhang Y, Wang X, Cichocki A. The

Changing Face of P300 BCIs: A Comparison of Stimulus Changes in a P300 BCI Involving Faces, Emotion, and Movement. PLoS One 7(11), 1-10 (2012).

74. Latchoumane C, Vialatte F, Sole-Casals J, Maurice M, Wimalaratna S, Hudson

N, Jeong J, Cichocki A. Multiway array decomposition analysis of EEGs in Alzheimer’s disease. Journal of Neuroscience Methods 207 (1), 41-50 (2012).

75. Nam Y, Zhao Q, Cichocki A. Tongue-Rudder: A Glossokinetic-Potential-Based

tongue-Machine Interface. IEEE Trans. on Biomedical Engineering 59 (1), 290-299 (2012).

76. Phan A-H, Cichocki A, Tichavsky P, Koldovsky Z. On Connection between the

Convolutive and Ordinary Nonnegative Matrix Factorizations. Lecture Notes in Computer Science, 7, 191, 288-296 (2012).

77. Phan A-H, Cichocki A, Tichavsky P, Mandic D, Matsuoka K. On Revealing

Replicating Structures in Multiway Data: A Novel Tensor Decomposition

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Approach. Lecture Notes in Computer Science 7191, 207-305 (2012).

78. Vialatte F, Dauwels J, Musha T, Cichocki A. Audio representations of multi-channel EEG: a new tool for diagnosis of brain disorders. American Journal of Neurodegenerative Disease 1 (3), 292-304 (2012).

79. Yokota T, Cichocki A, Yamashita Y. Linked PARAFAC/CP Tensor

Decomposition and Its Fast Implementation for Multi-block Tensor Analysis. Lecture Notes in Computer Science, 7665, 84-91 (2012).

80. Zhang Y, Zhao Q, Jin J, Wang X, Cichocki A. A Novel BCI Based on ERP

Components Sensitive to Configural Processing of Human Faces. Journal of Neural Engineering 9 (2), 026018 (2012).

81. Zhou G, Cichocki A, Xie S. Fast Nonnegative Matrix/Tensor Factorization

Based on Low-Rank Approximation. IEEE Trans. on Signal Processing 60 (6), 2928-2940 (2012).

82. Zhou G, Cichocki A. Canonical Polyadic Decomposition Based on a Single

Mode Blind Source Separation. IEEE Signal Processing Letters 19 (8), 523-526 (2012).

83. Zhou G, Cichocki A. Fast and unique Tucker decompositions via multiway blind

source separation. Bulletin of Polish Academy of Science 60 (3), 389-405 (2012).

2011

84. Cichocki A : "Tensors decompositions: New concepts for brain data analysis? ",

Journal of Control, Measurements, and System Integration (SICE), (invited paper), vol. 7, pp. 507-517 (July 2011).

85. Cichocki A., Cruces S., and Amari S-I.: "Generalized Alpha-Beta divergences

and their application to robust nonnegative matrix factorization", Entropy, vol. 13, pp. 134-170 (2011).

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86. Bakardjian H, Tanaka T, Cichocki A. "Emotional Faces Boost up Steady-state Visual Responses for Brain-Computer Interface". NeuroReport 22, 121-125 (2011).

87. He Z, Xie S, Zdunek R, Zhou G, Cichocki A. Symmetric Nonnegative Matrix Factorization: Algorithms and Applications to Probabilistic Clustering. IEEE Transactions on Neural Networks 22 (12), 2117-2131 (2011).

88. I. Kopriva, M. Hadžija, M.P. Hadžija, M. Korolija, and A. Cichocki: "Rational

variety mapping for contrast-enhanced nonlinear unsupervised segmentation of multispectral images of unstained specimen", The American Journal of Pathology, vol. 179, No. 2, pp 547-554 (June 2011).

89. A-H. Phan and A. Cichocki, "Extended HALS algorithm for nonnegative

Tucker decomposition and its applications for multiway analysis and classification" , Neurocomputing, vol. 74, No. 11, pp. 1956-1969, (May 2011).

90. A.H. Phan and A. Cichocki: "PARAFAC Algorithms for large-scale problems", Neurocomputing, vol. 74 (11), pp.1970-1984, 2011.

91. J. Dauwels, K. Srinivasan, M.R. Reddy, T. Musha, F. Vialatte, C. Latchoumane,

J. Jeong and A. Cichocki: "Slowing and Loss of Complexity in Alzheimer’s EEG: Two Sides of the Same Coin?," International Journal of Alzheimer's Disease, vol. 2011, Article ID 539621, 10 pages doi:10.4061/2011/539621 (2011).

92. F. Vialatte, J Dauwels, M. Maurice, T. Musha, and A. Cichocki: "Improving the specificity of EEG for diagnosing Alzheimer's Disease", International Journal of Alzheimer's Disease, vol. 2011, Article ID 259069, (April 2011).

93. Zhang Y, Zhou G, Zhao Q, Onishi A, Jin J, Wang X, Cichocki A. "Multiway Canonical Correlation Analysis for Frequency Components Recognition in SSVEP-Based BCIs". Lecture Notes in Computer Science 7062, 287-295 (2011).

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94. Zhao Q, Onishi A, Zhang Y, Cao J, Zhang L, Cichocki A. "A Novel oddball paradigm for affective BCIs Using Emotional Faces as Stimuli". Lecture Notes on Computer Science, 7062, 279-286 (2011)

2010 95. A. Cichocki, and S. Amari: “Families of Alpha-Beta-and Gamma-Divergences:

Flexible and Robust Measures of Similarities", Entropy, Vol.12 No.6, pp. 1532-1568, (2010).

96. S Amari and A. Cichocki. “Information Geometry of Divergence Function", Bulletin of the Polish Academy of Science (Technical Sciences), Vol. 58, No. 1, pp. 183-195, (2010).

97. A-H. Phan and A. Cichocki. “Tensor Decompositions for Feature Extraction and Classification of High Dimensional Datasets”, IEICE NOLTA, Vol. E93-N, No.1, pp 37-68, Oct. (2010).

98. C. Caiafa and A. Cichocki. "Generalizing the Column-Row Matrix Decomposition to Multi-way Arrays", Linear Algebra and its Applications, Vol. 433, Issue 3 pp.557-573, (2010).

99. Z. He, A. Cichocki, SL. Xie, and K Choi. “Detecting the number of clusters in n-way probabilistic clustering”, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), January 2010 vol. 32 (11), pp. 2006-2021.

2009

100. A. Cichocki, and A-H. Phan. “Fast Local Algorithms for Large Scale Nonnegative Matrix and Tensor Factorizations” IEICE Trans. Fundamentals, E92-A(3), 708-721, (invited paper) (2009).

101. C. Caiafa, and A. Cichocki. “Estimation of Sparse Non-negative Sources from Noisy Overcomplete Mixtures using MAP”, Neural Computation, 21 (12), 3487-3518 (2009)..

102. J. Dauwels, F. Vialatte, T. Weber, and A. Cichocki. “Quantifying Statistical Interdependance by Message Passing on Graphs, PART I: Algorithms and Applications to Neural Signals”, Neural Computation, 21, 2152-2202 (2009)

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103. J. Dauwels, F. Vialatte, T. Weber, and A. Cichocki. “Quantifying Statistical Interdependance by Message Passing on Graphs, PART II: Multi-Dimensional Point Processes”, Neural Computation, 21, 2202-2268 (2009).

104. J. Dauwels, F. Vialatte, T. Musha, and A. Cichocki. “A comparative study of synchrony measures for the early diagnosis of Alzheimer's disease based on EEG”, Neuroimage, 49, 668-693 (2009).

105. Z. He, A. Cichocki, R. Zdunek, and SL. Xie. “Improved FOCUSS Methods with Conjugate Gradient Iterations”, IEEE Trans. Signal Processing, 57(1), 399-404 (2009).

106. Z. He, A. Cichocki, YQ. Li, SL. Xie, and S. Sanei. “K-hyperline Clustering Learning for Sparse Component Analysis”, Signal Processing, 89, 1011-1022 (2009).

107. Z. He and A. Cichocki. “Efficient method for Tucker3 model selection”, Electronics Letters, 45 (15), 805-806, August 2009.

108. I. Kopriva, I. Jeric, and A. Cichocki. “Blind Decomposition of Infrared Spectra Using Flexible Component Analysis”, Chemometrics and Intelligent Laboratory Systems, 97, 170-178 (2009).

109. I. Kopriva and A. Cichocki. “Blind decomposition of low-dimensional multi-spectral image by sparse component analysis”, Journal of Chemometrics, Vol.23, Issue 11, pp. 590-597 (2009) (www.interscience.wiley.com) DOI: 10.1002/cem.1257.

110. I. Kopriva and A. Cichocki. “Blind multispectral image decomposition by 3D nonnegative tensor factorization”, Optics Letters, 34, No.14, pp. 2210-2212, July 15 2009.

111. H. Lee, A. Cichocki and S. Choi, “Kernel nonnegative matrix factorization for spectral EEG feature extraction”, Neurocomputing, 72 (13-15), pp. 3182-3190, (2009)

112. T. Rutkowski, A. Cichocki, T. Tanaka, A. Ralescu, and D. Mandic. “Clustering of Spectral Patterns Based on EMD Components of EEG Channels with Applications to Neurophysiological Signals Separation”, Lectures Notes in Computer Science, Springer LNCS-5506, 452-259 (2009).

113. T. Rutkowski, D. Mandic, A. Cichocki and A. Przybyszewski, “EMD approach to multichannel EEG data the amplitude and phase components clustering analysis”, Journal of Circuits, Systems, and Computers (2009).

114. B. Swiderski, S. Osowski, A. Cichocki A, and A. Rysz. “Single-class SVM and Directed Transfer Function Approach to the Localization of the Region

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Containing Epileptic Focus”, Neurocomputing, 72, 1575-1583 (2009). 115. F. Vialatte, H. Bakardjian, R. Prasad, and A. Cichocki. “EEG Paroxysmal

Gamma Waves during Bhramari Pranayama: a Yoga Breathing Technique”, Consciousness and Cognition (in press 2009).

116. F. Vialatte, J. Sole-Casals, J. Dauwels, M. Maurice, and A. Cichocki. “Bump Time-Frequency Toolbox: a Toolbox for Time-Frequency Oscillatory Bursts Extraction in Electrophysiological Signals”, BMC Neuroscience (2009). http://www.biomedcentral.com/content/pdf/1471-2202-10-46.pdf

117. F. Vialatte, J. Dauwels, M. Maurice, Y. Yamaguchi, and A. Cichocki. “On the Synchrony of Steady State Visual Evoked Potentials and Oscillatory Burst Events”, Cognitive Neurodynamics, vol 3 (3), 251-261 (2009).

118. W. Wang, A. Cichocki and J Chambers: “A Multiplicative Algorithm for Convolutive Non-Negative Matrix Factorization Based on Squared Euclidean Distance”, IEEE Transactions on Signal Processing, 57 (7), 2858-2864, July 2009.

119. Q. Zhao, L. Zhang L, and A. Cichocki: “EEG-based Asynchronous BCI Control of a Car in 3D Virtual Reality Environments”, Chinese Science Bulletin, 54, 78-87 (2009).

2008 120. Z. Chen, J. Cao, Y. Cao, Y. Zhang, F. Gu, G. Zhu, Z. Hong, B.

Wang, and A. Cichocki. “An Empirical EEG Analysis in Brain Death Diagnosis for Adults”, Cognitive Neurodynamics, 2, 257-271 (2008).

121. A. Cichocki, M. Jankovic, R. Zdunek, and S. Amari. “Sparse Super Symmetric Tensor Factorization”, Lecture Notes in Computer Science, Neural Information Processing, Springer LNCS-4984, 781-790 (2008).

122. A. Cichocki, A-H. Phan, R. Zdunek, and L.Q. Zhang. “Flexible Component Analysis for Sparse, Smooth, Nonnegative Coding or Representation”, Lecture Notes in Computer Science, Neural Information Processing, Springer, LNCS-4984, 811-820 (2008).

123. A. Cichocki, R. Zdunek, and S. Amari. “Nonnegative Matrix and Tensor Factorization”, IEEE Signal Processing Magazine, January, 142-145 (2008).

124. A. Cichocki A, H.K. Lee, Y.D. Kim, and S. Choi. “Nonnegative Matrix Factorization with Alpha-divergence”, Pattern Recognition Letters, 29(9), 1433-1440 (2008).

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125. A. Cichocki, Y. Washizawa, T. Rutkowski, H. Bakardjian, A-H. Phan, S. Choi, H. Lee, Q. Zhao, Z. Liqing, and Y. Li. “Noninvasive BCIs: Multiway Signal-processing Array Decompositions”, Computer, (invited paper), 41 (10), 34-42 (2008).

126. J. Dauwels, F. Vialatte, and A. Cichocki. “A Comparative Study of Synchrony Measures for the Early Detection of Alzheimer’s Disease Based on EEG”, Lecture Notes in Computer Science, Neural Information Processing, Springer, LNCS-4984, 112-125 (2008).

127. Z. He, S. Xie, L. Zhang, and A. Cichocki. “A note on Lewicki-Sejnowski Gradient for Learning Overcomplete Representations”, Neural Computation, 20(3), 636-643 (2008).

128. Z. He, A. Cichocki, R. Zdunek, and J. Cao. “CG-M-FOCUSS and Its Application to Distributed Compressed Sensing”, Lecture Notes in Computer Science, Advances in Neural Networks, Springer LNCS-5263, 237-245 (2008).

129. M. Jankovic, P. Martinez, Z. Chen, and A. Cichocki. “Modified Modulated Hebb-Oja Learning Rule: A Method for Biologically Plausible Principal Component Analysis”, Lecture Notes in Computer Science, Neural Information Processing, Springer LNCS-4984, 527-536 (2008).

130. YQ. Li, A. Cichocki, S. Amari, SL. Xie, and SL. Guan. “Equivalence Probability and Sparsity of Two Sparse Solutions in Sparse Representation”, IEEE Trans. Neural Networks, 19(12), 2009-2021 (2008).

131. P. Martinez, H. Bakardjian, M. Vallverdu, and A. Cichocki. “Fast Multi-command SSVEP Brain Machine Interface without Training”, Lecture Notes in Computer Science, Artificial Neural Networks, Springer LNCS-5164, 300-307 (2008).

132. M. Mouri, A. Funase, A. Cichocki, I. Takumi, H. Yasukawa, and M. Hata. “Global Signal Elimination and Local Signals Enhancement from EM Radiation Waves Using Independent Component Analysis”, IEICE Transactions on Fundamentals of Electronics”, Communications and Computer Sciences, 91(8), 1875-1882 (2008).

133. A-H. Phan, and A. Cichocki. “Fast and Efficient Algorithms for Nonnegative Tucker Decomposition”, Lecture Notes in Computer Science, Advances in Neural Networks, Springer, LNCS-5264, 772-782 (2008).

134. T. Rutkowski, D. Mandic, A. Cichocki, and A. Przybyszewski. “EMD Approach to Multichannel EEG Data – The Amplitude and Phase Synchrony Analysis Technique”, Lecture Notes in Computer Science, Advanced Intelligent

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Computing Theories and Applications, Springer, LNCS-5226, 122-129 (2008). 135. F. Vialatte, and A. Cichocki. “Split-Test Bonferroni Correction for QEEG

Statistical Maps”, Biological Cybernetics, 98, 295-303 (2008). 136. F. Vialatte, J. Solé-Casals, and A. Cichocki. “EEG Windowed

Statistical Wavelet Scoring for Evaluation and Discrimination of Muscular Artifacts”, Physiological Measurement, 29, 1435-1452 (2008).

137. Y. Washizawa, and A. Cichocki. “Sparse Blind Identification and Separation by Using Adaptive K-orthodrome Clustering”, Neurocomputing, 71, 2321-2329 (2008).

138. J. Xu, H. Bakardjian, A. Cichocki, and J. Principe. “A New Nonlinear Similarity Measure for Multichannel Signals”, Neural Networks, 21, 222-231 (2008).

139. R. Zdunek, and A. Cichocki. “Nonnegative Matrix Factorization with Quadratic Programming”, Neurocomputing, 71, 2309-2320 (2008).

140. R. Zdunek, and A. Cichocki. “Blind Image Separation Using Nonnegative Matrix Factorization with Gibbs Smoothing”, Lecture Notes in Computer Science, Neural Information Processing, Springer, LNCS-4985, 519-528 (2008).

141. R. Zdunek, and A. Cichocki. “Improved M-FOCUSS Algorithm with Overlapping Blocks for Locally Smooth Sparse Signals”, IEEE Trans. Signal Processing, 56(10), Part 1, 4752-4761 (2008).

2007 142. A. Cichocki, R. Zdunek, S. Choi, R. Plemmons, and S. Amari: ”Novel Multi-

layer Non-negative Tensor Factorization with Sparsity Constraints”, Lecture Notes in Computer Science, Springer, LNCS-4432, 271-280 (2007).

143. A. Cichocki, and R. Zdunek: ”Regularized Alternating Least Squares Algorithms for Non-negative Matrix/Tensor Factorization”, Lecture Notes in Computer Science, Vol. Springer, LNCS-4493, 793-802 (2007).

144. A. Cichocki, R. Zdunek, and S. Amari: ”Hierarchical ALS Algorithms for Nonnegative Matrix and 3D Tensor Factorization”, Lecture Notes in Computer Science, Springer, LNCS-4666, 169-176 (2007).

145. A. Cichocki, and R. Zdunek.: ”Multilayer Nonnegative Matrix Factorization using Projected Gradient Approaches”, International Journal of Neural Systems, Vol. 17, No. 6, 431-446 (2007).

146. L. Astolfi, H. Bakardjian, F. Cincotti, D. Mattia, M. Marciani, F. Fallani, A.

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Colosimo, S. Salinari, F. Miwakeichi, Y. Yamaguchi, P. Martinez, A. Cichocki, A. Tocci, F. Babiloni: ”Estimate of Causality between Independent Cortical Spatial Patterns during Movement Volition in Spinal Cord Injured Patients”, Brain Topography, 2007 Spring; 19(3):107-23 (2007).

147. Z. Chen, S. Ohara, J. Cao, F.B. Vialatte, F.A. Lenz and A. Cichocki, ”Statistical modeling and analysis of laser-evoked potentials of electrocorticogram recordings from awake humans”, Journal of Computational Intelligence and Neuroscience, 24 pages.

148. F. Fallani, L. Astolfi, F. Cincotti, D. Mattia, M. Marciani, S. Salinari, J. Kurths, S. Gao, A. Cichocki, A. Colosimo, and F. Babioni: ”Cortical Functional Connectivity Networks in Normal and Spinal Cord Injured Patients: Evaluation by Graph Analysis”, Human Brain Mapping, Vol. 28, Issue 12, 1334-1346 (2007).

149. D. Feng, W. Zheng, and A. Cichocki: ”Matrix-Group Algorithm via Improved Whitening Process for Extracting Statistically Independent Sources from Array Signals”, IEEE Transactions on Signal Processing, Vol. 55, No.3, 962-977 (2007).

150. P. Georgiev, P. Pardalos, and A. Cichocki, ”Algorithms with High Order Convergence Speed for Blind Source Extraction”, Journal of Computational Optimization and Applications, Vol. 38, No. 1, Vol. 38, No. 1, 123-131 (2007)

151. Z. He, S. Xie, S. Ding, and A. Cichocki, ”Convolutive Blind Source Separation in the Frequency Domain Based on Sparse Representation”, IEEE Transactions on Audio, Speech, and Language Processing, Vol. 15, No. 5, July 2007, pp. 1551-1563

152. Z. He, and A. Cichocki: ”An Efficient K-Hyperplane Clustering Algorithm and Its Application to Sparse Component Analysis”, Lecture Notes in Computer Science, Springer, LNCS-4492, 1032-1041 (2007).

153. H. Lee, Y.-D. Kim, A. Cichocki, and S. Choi, ”Nonnegative Tensor Factorization for Continuous EEG Classification,” International Journal of Neural Systems, Vol. 17, No. 4, pp. 1-13, (2007).

154. W. Liu, D.P. Mandic, and A. Cichocki: ”Blind Source Extraction Based on a Linear Predictor”, IET Signal Processing, Vol. 1, No. 1, 29-34 (2007).

155. W. Liu, D. Mandic, and A. Cichocki: ”Analysis and Online Realization of the CCA Approach for Blind Source Separation”, IEEE Transactions of Neural Networks, Vol. 8, No. 5, 1505-1510 (2007).

156. P. Martinez, H. Bakardjian and A Cichocki, ”Fully-Online, Multi-Command

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Brain Computer Interface with Visual Neurofeedback Using SSVEP Paradigm”, Journal of Computational Intelligence and Neuroscience, 2007.

157. S. Osowski, B. Swiderski, A. Cichocki, and A. Rysz: ”Epileptic Seizure Characterization by Lyapunov exponent of EEG signal”, Compel, Vol. 26, No. 6 , 1226-1287 (2007).

158. T.M. Rutkowski, R. Zdunek, and A. Cichocki, ”Multichannel EEG Brain Activity Pattern Analysis in Time-Frequency Domain with Nonnegative Matrix Factorization Support”, International Congress Series, Elsevier, Vol. 1301, 2007, pp. 266-269

159. A. Seghouane, and A. Cichocki: ”Bayesian estimation of the number of principal components”, Signal Processing, Vol. 87, 562-568 (2007).

160. H. Takeichi, S. Koyama, A. Matani, and A. Cichocki, ”Speech Comprehension Assessed by Electroencephalography: A New Method using m-sequence Modulation”, Neuroscience Research, Vol. 57, 2007, pp. 314-318.

161. F. Theis, P. Georgiev, and A. Cichocki: ”Robust Sparse Component Analysis Based on a Generalized Hough Transform”, EURASIP Journal on Advances in Signal Processing (2007).

162. Y. Washizawa, and A. Cichocki: ”Sparse Blind Identification and Separation by Using Adaptive K-orthodrome Clustering”, Neurocomputing (2007).

163. W.L. Woon and A. Cichocki, ”Novel Features for Brain Computer Interfaces”, Journal of Computational Intelligence and Neuroscience (2007).

164. W.L. Woon, A. Cichocki, F. Vialatte, and T. Musha, ”Techniques for Early Detection of Alzheimer’s Disease Using Spontaneous EEG Recordings”, Physiological Measurements, Vol. 28, No. 4, April 2007, pp. 335-347.

165. R. Zdunek, and A. Cichocki: ”Nonnegative Matrix Factorization with Constrained Second-order Optimization”, Signal Processing, Vol. 87, No.8, 1904--1916 (2007).

166. J-H. Park, S. Kim, Ch-H. Kim, A. Cichocki, and K. Kim: ”Multiscale Entropy Analysis of EEG from Patients under Different Pathological Conditions”, Fractals, Vol. 15, No. 4, 399-404 (2007).

2006

167. A. Cichocki and R. Zdunek, ”Multilayer Nonnegative Matrix Factorization”, Electronics Letters, Vol. 42, No. 16 (2006), pp. 947-948.

168. Y. Li, A. Cichocki, and S. Amari, ”Blind Estimation of Channel Parameters and Source Components for EEG Signals: A Sparse Factorization Approach”,

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IEEE Transactions on Neural Networks, Vol. 17, No. 2, March 2006, pp. 419-431.

169. Y. Li, S. Amari, A. Cichocki, D. W. C. Ho, and S. Xie, ”Underdetermined Blind Source Separation Based on Sparse Representation”, IEEE Transactions On Signal Processing, Vol. 54, No. 2, February 2006, pp 423-437.

170. Y. Li, S. Amari, A. Cichocki, and C. Guan, ”Probability Estimation for Recoverability Analysis of Blind Source Separation Based on Sparse Representation”, IEEE Transactions on Information Theory52(7), pp. 3139-3152 (2006).

171. S. Ding, J. Huang, D. Wei, and A. Cichocki, ”A Near Real-Time Approach for Convolutive Blind Source Separation”, IEEE Transactions on Circuits and Systems I, Vol. 53, No. 1, January 2006, pp. 114-128.

172. S. Ding, A. Cichocki, J. Huang, and D.Wei, ”Blind Source Separation of Acoustic Signals in Realistic Environments Based on ICA in the Time-Frequency Domain”, Journal of Pervasive Computing and Communications, Vol. 1, No. 2, June 2005, pp. 89-99.

173. M.G. Jafari, W. Wang, J.A. Chambers, T. Hoya, and A. Cichocki, ”Sequential Blind Source Separation Based Exclusively on Second-Order Statistics Developed for a Class of Periodic Signals”, IEEE Transactions On Signal Processing, Vol. 54, No. 3, March 2006, pp. 1028-1040.

2005

174. S. Choi, A. Cichocki, H.M. Park and S.-Y. Lee, ”Blind Source Separation and Independent Component Analysis: A Review”, Neural Information Processing - Letters and Reviews, Vol. 6, No.1, pp.1-57, January 2005.

175. A. Cichocki, S. L. Shishkin, T. Musha, Z. Leonowicz, T. Asada, and T. Kurachi: ”EEG Filtering Based on Blind Source Separation (BSS) for Early Detection of Alzheimer’s Disease”, Clinical Neurophysiology, Vol. 116, 2005, pp. 729737.

176. T. Hoya, T. Tanaka, A. Cichocki, T. Murakami, G. Hori, and J. A. Chambers: Stereophonic Noise Reduction Using A Combined Sliding Subspace Projection and Adaptive Signal Enhancement, IEEE Transactions on Speech and Audio Processing, Vol. 13, No. 3, pp. 309-320, May 2005.

2004

177. A. Cichocki. Blind Signal Processing Methods for Analyzing Multichannel

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Brain Signals. International Journal of Bioelectromagtism, 6(1), 2004. 178. S. A. Crucez-Alvarez, A. Cichocki, and S. Amari: ”From Blind Signal

Extraction to Blind Instantaneous Signal Separation: Criteria, Algorithms and Stability”, IEEE Transactions on Neural Networks, Special issue on Information Theoretical Learning, Vol. 15, No. 4, pp. 859-873, 2004.

179. Y. Li, A. Cichocki, and S. Amari: ”Analysis of Sparse Representation and Blind Source Separation”, Neural Computation, Vol. 16, No. 6, pp. 1193-1234, June 2004.

180. Y. Li, A. Cichocki, and L. Zhang, ”Blind Source Estimation of FIR Channels for Binary Sources: Grouping Decision Approach,” Signal Processing, 84, 2245-2263 (2004).

181. Y. Li, J. Wang, and A. Cichocki ”Blind Source Extraction from Convolutive Mixtures in Ill-conditioned Multi-Input Multi-Output Channels,” IEEE Trans. on Circuits and Systems, Vol.51, No.9. pp.1814-1822, Sept. 2004.

182. L. Zhang, A. Cichocki, and S. Amari, ”Multichannel Blind Deconvolution of Nonminimum-phase Systems Using Filter Decomposition,” IEEE Transactions on Signal Processing, vol. 52, no. 5, pp. 1430-1442, 2004.

183. L. Zhang, A. Cichocki, and S. Amari, ”Self-adaptive Blind Source Separation Based on Activation Functions Adaptation,” IEEE Transactions on Neural Networks, vol. 15, no. 2, pp. 233-244, 2004.

2003

184. A. Cichocki and P. Georgiev: Blind source separation with matrix constraints, IEICE Trans. Fundamentals, vol. E86-A, no. 3, March 2003.

185. R.R Gharieb and A. Cichocki: Second-order statistics based blind source separation using a bank of subband filters, Digital Signal Processing, vol.13, pp. 252-274, 2003.

186. S. Choi, A. Cichocki, L. Zhang and S. Amari: Approximate maximum likelihood source separation using the natural gradient, IEICE Trans. Fundamentals, vol. E86-A, No. 1, Jan. 2003.

2002

187. S. Cruces-Alvarez, A. Cichocki and S. Amari: On a new blind signal extraction

algorithm: Different criteria and stability analysis, IEEE Signal Processing Letters, vol. 9 No.8, August 2002, pp. 233-236.

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188. J. Cao, N. Murata, S. Amari, A. Cichocki and T. Takeda: Independent component analysis for single-trial MEG data decomposition and single-dipole source localization, Neurocomputing, vol.49, 2002, pp. 255-277.

189. S. Choi, A. Cichocki and S. Amari: Equivariant nonstationary source separation, Neural Networks, vol.15, 2002, pp.121-130.

190. S. Choi, A. Cichocki and A. Beluochrani: Second order non-stationary source separation, Journal of VLSI Signal Processing, 2002, vol. 32, no. 1-2, Aug. 2002, pp. 93-104.

191. S. Cruces, L. Castedo and A. Cichocki: Robust blind source separation algorithms using cumulants, Neurocomputing, vol. 49, Dec. 2002, pp.87-118.

192. S. A. Vorobyov and A. Cichocki: Blind noise reduction for multi-sensory signals using ICA and subspace filtering with application to EEG analysis, Biological Cybernetics, Vol. 86, No. 4, April 2002, pp.293-303.

193. L. Zhang, A. Cichocki and S. Amari: Geometrical structures of FIR manifold and their application to multichannel blind deconvolution, Journal of VLSI for Signal Processing, Vol. 31, 2002, pp.31-44.

2001

194. A. K. Barros and A. Cichocki: Extraction of specific signals with temporal structure, Neural Computation, Vol. 13, No. 9, September 2001, pp. 1995-2000.

195. S. Choi and A. Cichocki: Blind equalization via approximate maximum likelihood source separation, Electronics Letters, Vol. 37, No. 1, January 27, 2001, pp. 61-62.

196. S. Choi and A. Cichocki : Algebraic differential decorrelation for non-stationary source separation, Electronics Letters, vol. 37, no. 23, November 18, 2001, pp. 1414-1415,

197. R. R. Gharieb and A. Cichocki: Noise reduction in brain evoked potentials based on third-order correlations, IEEE Transactions on Biomedical Engineering, Vol. 48, 2001, pp. 501-512.

198. R. R. Gharieb and A. Cichocki: Segmentation and tracking of EEG signal using an adaptive recursive bandpass filter, International Federation for Medical & Biological Engineering & Computing, Vol. 39, 2001, pp. 237-248.

199. R. Rosipal, M. Girolami, L.J. Trejo and A. Cichocki: Kernel PCA for feature extraction and de-noising in non-linear regression, Neural Computing and Applications, Vol. 10, pp. 231-243.

200. S.A. Vorobyov and A. Cichocki: Hyper radial basis function neural networks

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for interference cancellation with nonlinear processing of reference signal, Digital Signal Processing, Academic Press, Vol. 11, No. 3, July 2001, pp. 204-221.

201. S.A. Vorobyov, A. Cichocki and Ye.V. Bodyanskiy: Adaptive noise cancellation for multi-sensory signals, Journal of Fluctuation and Noise Letters, Vol. 1, No. 1, 2001, pp.12-24.

202. L. Zhang, S. Amari and A. Cichocki: Semiparametric model and super-efficiency in blind deconvolution, Signal Processing, Vol. 81, 2001, pp. 2535-2553.

2000

203. S. Amari, , T.-P. Chen and A. Cichocki: Nonholonoimic orthogonal learning algorithms for blind source separation. Neural Computation, Vol. 12, 2000, pp.1463-1484.

204. A. Belouchrani and A. Cichocki: Robust whitening procedure in blind source separation context, Electronics Letters, Vol. 36, No. 24, 2000, pp. 2050-2053.

205. J. Cao, A. Cichocki and S. Tanaka: Self-scaling and self-adaptive compact time-delay neural network for dynamical nonlinear and nonstationary system identification, Journal of Signal Processing, Vol. 4, No. 1, 2000, pp. 37-43.

206. J. Cao, N. Murata and A. Cichocki: Independent component analysis algorithm for on-line blind separation and blind equalization systems, Journal of Signal Processing, Vol. No. 2, March, 2000, pp.131-140.

207. J. Cao, N. Murata, S. Amari, A. Cichocki, T. Takeda, H. Endo and N. Harada: Single-trail magnetoencephalographic data decomposition and localization based on independent component analysis approach. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, No. 9, 2000, pp.1757-1766.

208. S. Choi, S. Amari and A. Cichocki: Natural gradient learning for spatio-temporal deceleration: recurrent network, IEICE Trans. Fundamentals, vol. E83-A, no. 12, Dec. 2000, pp. 2715-2722.

209. S. Choi and A. Cichocki: Blind separation of non-stationary sources in noisy mixtures, Electronics Letters, Vol. 36, No. 9, April, 2000, pp. 848-849.

210. S. Choi, A. Cichocki and S. Amari. Flexible independent component analysis. Journal of VLSI Signal Processing, Vol. 26, 2000, pp. 25-38.

211. A. Cichocki and R. Thawonmas: On-line algorithm for blind signal extraction of arbitrarily distributed, but temporally correlated sources using second order

30

statistics. Neural Processing Letters, Vol. 12, August 2000, pp.91-98. 212. S. Cruces, A. Cichocki and L. Castedo: An iterative inversion approach to

blind source separation . IEEE Transactions on Neural Networks, Vol. 11, No. 6, 2000, pp.1423-1437.

213. L. Zhang and A. Cichocki: Blind deconvolution of dynamical systems: A state space approach, (invited paper), Journal of Signal Processing, Vol. 4, No. 2, Mar. 2000, pp. 111-130.

a. 1999

214. S. Choi and A. Cichocki: An unsupervised hybrid network for blind separation of independent non-Gaussian source signals in multi-path environment, Journal of Communications and Networks, Vol. 1, No. 1, March 1999, pp. 19-25.

215. S. Choi and A. Cichocki: Hybrid learning approach to blind deconvolution of linear MIMO systems, Electronics Letters, Vol. 35, No. 17, 1999, pp. 1429-1430.

216. A. Cichocki, J. Karhunen, W. Kasprzak and R. Vigario: Neural networks for blind separation with unknown number of sources, Neurocomputing, Vol. 24, 1999, pp. 55-93.

217. S.C. Douglas, A. Cichocki and S. Amari: Self-whitening algorithms for adaptive equalization and deconvolution, IEEE Trans. on Signal Processing, Vol. 47, No. 4, April 1999, pp. 1161-1165.

218. S. Osowski, A. Cichocki: Learning in dynamic neural networks using signal flow graphs, Int. Journal of Circuit Theory and Applications, Vol. 27, 1999, pp. 209-228.

219. R. Thwanomas and A. Cichocki: Blind signal extraction of arbitrary distributed but temporally correlated signals - neural network approach, IEICE Transactions, Fundamentals, vol. E82 A, No.9, Sept. 1999, pp. 1834-1844.

1998

220. S. Amari and A. Cichocki: Adaptive blind signal processing - neural network approaches, Proceedings IEEE (invited paper), vol.86, No.10, Oct. 1998, pp.2026-2048.

221. S. Choi and A. Cichocki: Cascade neural networks for multichannel blind deconvolution, Electronics Letters, vol. 34, No. 12, 1998, pp. 1186-1187.

222. S. Choi, R.-W. Liu and A. Cichocki: A spurious equilibria-free learning algorithm for the blind separation of non-zero skewness signals, Neural

31

Processing Letters, vol.7, no. 2, Jan. 1998, pp. 61-68. 223. A. Cichocki: Blind identification and separation of noisy source signals -

neural networks approaches, ISCIE Journal, Japan, 1998, vol.42, No.2, 1998, pp. 63-73.

224. A. Cichocki, S. Douglas and S. Amari: Robust techniques for independent component analysis (ICA) with noisy data, Neurocomputing, vol. 22, 1998, pp. 113-129.

225. A. Cichocki, P. Kostyla, T Lobos and Z. Waclawek: Neural networks for real-time estimation of parameters of signals in power systems, Int. Journal of Engineering Intelligent Systems for Electrical Engineering and Communication, Vol. 6, No. 3, 1998, pp. 131-140.

226. S.C. Douglas, A. Cichocki and S. Amari: A bias removal technique for blind source separation with noisy measurements, Electronics Letters, Vol. 34, No. 14, 9 July 1998, pp. 1379-1380.

227. M. Girolami, A. Cichocki and S. Amari: A common neural network model for unsupervised exploratory data analysis and independent component analysis, IEEE Trans. on Neural Networks, vol. 9, No. 6, 1998, pp. 1495-1501.

228. R. Thawonmas, A. Cichocki and S. Amari: A Cascade neural network for blind signal extraction without spurious equilibria, IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, vol. E81-A, No. 9, September 1998, pp. 1833-1846.

229. L. Zhang, A. Cichocki and S. Amari: Natural gradient algorithm for blind separation of overdetermined mixture with additive noise, IEEE Signal Processing Letters, Vol. 6, No. 11, 1999, pp. 293-295. 1998

1997-1995 230. S. Amari, T.-P. Chen and A. Cichocki: Stability analysis of adaptive blind

source separation, Neural Networks, vol.10, No.8, 1997, pp. 1345-1351. 231. A. Cichocki, R. Thawonmas and S. Amari: Sequential blind signal extraction in

order specified by stochastic properties, Electronics Letters, vol.33, No.1, Jan. 1997, pp. 64-65.

232. A. Cichocki, R.E. Bogner, L. Moszczynski and K. Pope: Modified Herault-Jutten algorithms for blind separation of sources, Digital Signal Processing, vol.7, No.2, April 1997, pp. 80-93.

233. A. Cichocki and A. Bargiela: Neural networks for solving linear inequality

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systems, Int. Journal of Parallel Computing, vol. 22, 1997, pp. 1455-1475. 234. A. Cichocki, S. Amari and J. Cao: Neural network models for blind separation

of time delayed and convolved signals, IEICE Transactions on Fundamentals of Electronics, Communications Computer Sciences, vol. E80-A, No. 9, 1997, pp. 1595-1603.

235. S.C. Douglas and A. Cichocki: Neural networks for blind decorrelation of signals, IEEE Trans, on Signal Processing, vol. 45, No, 11, Nov. 1997, pp. 2829-2842.

236. S.C. Douglas and A. Cichocki: On-line step size selection for training adaptive systems, IEEE Signal Processing Magazine, Vol. 14, No. 6, November 1997, pp. 45-46.

237. J. Karhunen, A. Cichocki, W. Kasprzak and P. Pajunen: On neural blind separation with noise suppression and redundancy reduction, in Int. J. of Neural Systems, vol.8, No.2, April 1997, pp. 219-237.

238. W. Kasprzak, A. Cichocki and S. Amari: Blind source separation with convolutive noise cancellation, Journal of Neural Computing and Applications, vol. 3, No. 6, Nov. 1997, pp. 127-141.

239. F.-L. Luo, R. Unbehauen and A. Cichocki: A minor component analysis algorithm, Neural Networks, vol.10, No.2, March 1997, pp. 291-297.

240. H.H. Yang, S. Amari and A. Cichocki: Information-theoretic approach to blind separation of sources in non-linear mixture, Signal Processing, vol.64, No.3, 1998, pp. 291-300.1997

1996

241. S. Osowski and A. Cichocki: Ladder network design through optimization, Bull. of Polish Academy of Sciences, 1997, Vol. 45, pp. 403 - 415. 1996

242. A. Cichocki and R. Unbehauen: Robust neural networks with on-line learning for blind identification and blind separation of sources, IEEE Trans. on Circuits and Systems - I: Fundamental Theory and Applications, vol.43, Nov. 1996, pp. 894-906.

243. A. Cichocki and W. Kasprzak: Nonlinear learning algorithms for blind separation of natural images, Neural Network World, vol.6 1996, No.4, IDG Co., Prague, pp. 515-523. 13

244. A. Cichocki, R. Unbehauen, K. Weinzierl and R. Hoelzel: A new neural network for solving linear programming problems, European Journal of Operational Research, Elsevier Science B.V., The Netherlands, vol. 9, 1996, pp.

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244-256. 245. S.C. Douglas, A. Cichocki and S. Amari: Fast-convergence filtered regressor

algorithms for blind equalization, Electronics Letters, vol.32, No.23, Nov.1996, pp. 2114-2115.

246. W. Skarbek, A. Cichocki: Image Associative memory by recurrent neural subnetworks, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, IEICE Publ., Tokyo, vol. E79-A, (10) 1996, pp. 1638-1646.

247. W. Skarbek, A. Cichocki and W. Kasprzak: Principal subspace analysis for incomplete image data in one learning epoch, Neural Network World, vol. 6 (1996), No.3, IDG Co., Prague, pp. 375-382.

248. W. Skarbek and A. Cichocki: Robust image association by recurrent neural networks, Neural Processing Letters, Kluwer Academic Publishers, NL, vol.3, No.3, 1996, pp. 131-138.

1995

249. A. Cichocki, R. Unbehauen, M. Lendl and K. Weinzierl: Neural networks for linear inverse problems with incomplete data especially in applications to signal and image reconstruction, Neurocomputing, vol. 8, 1995, Elsevier Science B.V., pp. 7-41.

250. A. Cichocki, T. Kaczorek and J. Mazurek: Analog neural networks for solving in real-time linear inverse and total least squares problems, Journal of Applied Mathematics and Computation Science, vol. 5, 1995, No.1, PAS Publ. Wroclaw, Poland, pp. 105-138.

1994

251. A. Cichocki and T. Lobos: Artificial neural networks for real - estimation of basic wave-forms of voltages and currents, IEEE Transactions on Power Systems, vol. 9, no. 2, May 1994, pp. 612-618.

252. A. Cichocki, R. Unbehauen and E. Rummert: Robust learning algorithm for blind separation of signals, Electronics Letters, vol. 30, no. 17, Aug.1994, pp. 1386-1387.

253. A. Cichocki and T. Kaczorek: Applications of neural - type structured networks for solving algebraic matrix equations and computation of Drazin inverse, Applied Mathematics and Computer Science, vol. 4, no. 3, 1994, pp. 309-330.

254. A. Cichocki and R. Unbehauen: Simplified neural networks for solving linear

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least squares and total least squares problems in real-time, IEEE Transactions on Neural Networks, vol.5, no. 6, Nov. 1994, pp. 910-923.

255. A. Cichocki, R. Unbehauen, and A. Krzyzak: Neural networks with on-chip learning for robust estimation of principal components in real time, Journal of Artificial Neural Systems, vol. 1, no. 1, pp. 1-23, 1994.

1993-1990

256. A. Cichocki and R. Unbehauen, Robust estimation of principal components in real time, Electronics Letters, vol.29, No.21, 1993, pp.1869-1870.

257. A. Cichocki and R. Unbehauen: Neural networks for solving systems of linear equations - Part II, IEEE Trans. on Circuits and Systems Analog and Digital Signal Processing, vol.39, No.9 Sept. 1992, pp.619-633.

258. A. Cichocki and L. Moszczynski: New learning algorithm for blind separation of sources, Electronics Letters, vol.28, No.21, Oct.1992, pp.1986-1988.

259. A. Cichocki and T. Lobos: Adaptive analogue network for real-time estimation of basic waveforms of voltages and currents, IEE Proc. C vol.139, No.4, July 1992, pp.343-350.

260. A. Cichocki, T. Kaczorek and A. Stajniak: Computation of Drazin inverse of singular matrix by using neural networks, Bulletin of Polish Academy of Science, Vol.40, No.4, 1992, pp.387-394.

261. A. Cichocki and T. Kaczorek: Neural-type structured networks for solving algebraic Riccati equations, Archives of Control Science, vol.1, N0.3-4, 1992, pp.153-165.

262. A. Cichocki and R. Unbehauen, Neural networks for solving systems of linear equations - Part II, IEEE Trans. on Circuits and Systems Analog and Digital Signal Processing, vol.39, No.9 Sept. 1992, pp.619-633.

263. A. Cichocki and R. Unbehauen: Switched-capacitor transducers with digital or duty-cycle output based on pulse-width modulation technique, Int. Journal of Electronics, vol.71, No.2, 1991, pp.265-278.

264. A. Cichocki and R. Unbehauen: Switched-capacitor interface for capacitive sensors based on relaxation oscillators, IEEE Trans. on Instrumentation and Measurement, Oct.1990, vol.IM-39, No.5, pp.797-799.

265. A. Cichocki and R. Unbehauen: Application of switched capacitor self-oscillating circuits to the conversion of R,L,C parameters into a frequency or digital signal, Int. Journal of Sensors and Actuators, July 1990, vol. A 24, pp. 129-137.

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1989-1974 266. A. Cichocki and R. Unbehauen: Technique for compensation of errors in

analogue multipliers, Electronics Letters, vol.25, No.5, 1989, pp.305-307. 267. A. Cichocki and R. Unbehauen: Switched-capacitor function generators, Int. J.

Electronics ,vol.64, No.3, 1988, pp.359-375. 268. A. Cichocki and R. Unbehauen: Logarithmic and exponential switched -

capacitor converters and some of their applications, IEE Proceedings Circuits and Systems, vol.135, Pt.G, No.2, 1988, pp.58-64.

269. A. Cichocki and R. Unbehauen: Monolithic MOS switched capacitor micro-systems for nonlinear signal processing, IEEE Transaction on Instrumentation and Measurement, vol.37, No.1, March 1988, pp.18-24.

270. S. Osowski, A. Cichocki and S. Filipowicz: Some aspects of nonlinear function simulation (in Polish), Rozprawy Elektrotechniki, 1988, vol. XXXIV, pp. 803-818.

271. A. Cichocki and R. Unbehauen: Simplified analysis of arbitrary switched –capacitor networks, IEE Proc. vol.134, Pt.G, No.1, 1987, pp.45-53. 15

272. S. Osowski and A. Cichocki: Explicit formulas for the tridiagonal systems and their applications, Bul. Acad. Pol. ser. Sci, vol. 35 1987, No. 11, pp. 725 - 745.

273. A. Cichocki, F. Strauss and R. Unbehauen: Realization of arbitrary linear resistive multi-ports using a switched-capacitor technique, International Journal of Electronics, vol.60, No.4, 1986, pp.463-480.

274. A. Cichocki and R. Unbehauen: A novel switched-capacitor four-quadrant multiplier-divider and some of its applications, IEEE Trans. Instrumentation and Measurement, vol.IM-35, No.2, 1986, pp.156-162.

275. A. Cichocki and R. Unbehauen: MOS SC micro-system for generating of trigonometric functions and their inverses, Electronics Letters, vol.22, No.20, 1986, pp.1056-1057.

276. R. Unbehauen and A. Cichocki: Ein Beitrag zur Synthese von SC -Netzwerken zurlinearen und nichtlinearen Signalverabeitung, NTZ Archiv, Bd.8, H.11, 1986, pp.271-286.

277. A. Cichocki and R. Unbehauen: Equivalent transformation of ladder-type networks, NTZ Archiv, Band 7, H.11, 1985, pp.125-284.

278. A. Cichocki and R. Unbehauen: Novel switched-capacitor generalized integrator, Electronics Letters, vol.21, 1985, pp.158-159.

279. A. Cichocki and R. Unbehauen: Design of precision switched-capacitor

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generalized integrator and their application to the synthesis of nonlinear networks, Proc. IEE, Electronic Circuits and Systems, Part G, vol.132, 1985, pp.225-236.

280. A. Cichocki: A sinusoidal frequency multiplying and dividing technique, Int. Journal of Electronics, vol.54, No.3, 1983, pp.427-436.

281. A. Cichocki: Nested-feedback loops realization of 2-D systems, , Circuits Systems and Signal Processing, vol.1, No.3-4, 1982, pp.321-343.

282. A. Cichocki: Synthesis of nonlinear functions using continued fraction technique, Electronics Letters, vol.16, No.11, 1981, pp.431-432.

283. A. Cichocki and S. Osowski: Some explicit formulas for the cascade of nonreciprocal 2-ports, Alta Frequenza, 1978, vol.47, No. 7.

284. A. Cichocki and S. Osowski: Matrix Coates flow graphs, IEE Proc. Electronic Circuits and Systems, 1978, vol. 2, No. 6.

285. A. Cichocki and S. Osowski: Analysis of active networks using flow graph technique, Electronics Letters, 1978, vol. 14, No. 7.

286. A. Cichocki and S. Osowski: Synthesis of active multiport network transfer function, Electronics Letters, 1978, vol. 14, No. 20.

287. A. Cichocki and S. Osowski: Synthesis of hybrid matrix of the general active RC N-port, AEU, 1978, vol.32, h. 2.

288. A. Cichocki and S. Osowski: Matrix continuants, some properties and applications, AEU, 1977, vol. 31, Heft 10.

289. A. Cichocki and S. Osowski: Analysis of cascade connection of non-alike 2-ports, IEEE Trans. on CAS, 1977, vol. 24, No. 5.

290. A. Cichocki, S. Osowski and S. Filipowicz: Analogue simulation of the nonlinear transfer characteristics, IEE Proc. Electronic Circuits and Systems, 1978, vol. 2, No. 1.

291. A. Cichocki and S. Osowski: Synteza N-wrotnika o wielokanalowej strukturze RC ze wzmacniaczami napieciowymi, Rozprawy Elektrotechniki, 1978, t. 24, z. 2.

292. A. Cichocki and S. Osowski: Synthesis of rational transfer matrices with active RC networks, Int. J. of Electronics, 1977, vol. 42, No. 3.

293. A. Cichocki, S. Osowski S. and S. Filipowicz: Unified active structure for an arbitrary 2-port network realization, Electronics Letters, 1977, vol. 13, No. 11.

294. A. Cichocki and S. Osowski: Synthesis of an arbitrary voltage transfer function, Int. J. of Electronics, 1976, vol. 41, No. 1.

295. Cichocki A., Osowski S., Zastosowanie kontynuanty blokowej do analizy

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lancuchowego polaczenia 2m-wrotnikow (in Polish), Archiwum Elektrotechniki, 1977, t. 26, z. 2.

296. A. Cichocki and S. Osowski: Analysis of active ladder network by using Coates flow graphs and continuants, Int. J. for Numerical Methods in Engineering, 1977, vol. 11, pp.900 - 904.

297. A. Cichocki and S. Osowski: Algorytm wyznaczania dowolnej transmitancji ukladu drabinkowego przy pomocy kontynuanty (in Polish), Archiwum Elektrotechniki, 1974, t. 23, z.4.

Book Chapters [1] A. Cichocki, Generalized Component Analysis and Blind Source Separation Methods for Analyzing Multichannel Brain Signals a chapter in the monograph, ”Statistical and Process Models of Cognitive Aging”, Notre Dame Series on Quantitative Methods, Editors: M.J Wenger and C. Schuster, (Mahwah, NJ: Erlbaum, 2006), http://www.bsp.brain.riken.jp/book.html [2] P.G. Georgiev, A. Cichocki and H Bakardjian: ”Optimization techniques for independent component analysis with applications to EEG data”, Quantitative Neuroscience: Models, Algorithms, Diagnostics, and Therapeutic Applications, Kluwer Academic, Boston, USA, 53-68 (2004). [3] A. Cichocki: ”Blind signal processing in application to biomedical signals, images and time series analysis: models and learning algorithms, 2nd European Interdisciplinary School on Nonlinear Dynamics for System and Signal Analysis (EUROATTRACTOR 2001), Pabst Science Publishers, Lengerich, 107-122 (2003). [4] S. Cruces, A. Cichocki, S.-I. Amari: The minimum entropy and cumulant based contrast functions for blind source extraction, in the book Bio-Inspired Applications of Connectionism, J. Mira and A. Prieto editors, Lecture Notes in Computer Science, Springer-Verlag. [6th International Work-Conference on Artificial and Natural Neural Networks (IWANN’2001)], vol. II, Granada, Spain, June 2001. (ISBN: 3-540-42237-4, ISSN: 0302-9743), pp. 786-793. [5] L. Zhang, S. Amari and A. Cichocki: Equi-convergence algorithm for blind separation of sources with arbitrary distributions, In the book Bio-Inspired Applications of Connectionism, Lecture Notes in Computer Science, Springer-Verlag. [6th International Work-Conference on Artificial and Natural Neural Networks (IWANN’2001)], vol. II, LNCS 2085, J. Mira & A. Prieto (Eds), Springer, 2001, pp. 826-833. [6] S. Amari, A. Cichocki and H.H. Yang: Blind Signal Separation and Extraction –

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Neural and Information Theoretic Approaches, Chapter 3 in the book Unsupervised Adaptive Filtering, S. Haykin (Editor), John Wiley, 2000, Vol. 1, pp. 63-138. [7] L. Zhang, A. Cichocki and S. Amari. Semiparametric approach for blind deconvolution of nonminimum phase systems. NIPS’99, Advances in Neural Information Processing 12, eds. by S.A. Solla, T.K. Leen and K.-R. Muller, MIT Press, 2000, pp. 363-369. [8] O. Jahn, A. Cichocki, A. A. Ioannides and S. Amari: Identification and elimination of artifacts from MEG signals using efficient independent component analysis, In the book: Recent Advances in Biomagnetism, Proc. 11th Int. Conf. on Biomagnetism, edited by T. Yoshimoto, M. Kotani, S. Kuriki, H. Karibe and N. Nakasato, Tohoku University Press, Sendai, Japan, 1999, pp. 224-227. [9] L. Zhang and A. Cichocki: Blind separation of filtered sources using state-space approach, in the book: Advances in Neural Information Processing Systems, eds. by M. S. Kearns, S. A. Solla and D. A. Cohn, The MIT Press, Cambridge, Vol. 11,1999, pp. 648-654. [10] A. Cichocki, J. Cao, S. Amari, N. Murata, T. Takeda and H. Endo: Enhancement of magnetoencephalographic signals using independent component analysis, In the book: Recent Advances in Biomagnetism, Proc.11th Int. Conf. on Biomagnetism, Eds. by T. Yoshimoto, M. Kotani, S. Kuriki, H. Karibe, and N. Nakasato, Tohoku University Press, Sendai, Japan, 1999, pp. 169-172. Selected List of Conference Papers in International Conference Proceedings [1] C. Caiafa and A. Cichocki: "Methods for Factorization and Approximation of Tensors by Partial Fiber Sampling", The Third International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP-2009, Dec. 13-16, 2009 Aruba. [2] A.H. Phan and A. Cichocki : "Fast Nonnegative Tensor Factorization for Very Large-Scale Problems Using Two-Stage Procedure", The Third International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP-2009, Dec. 13-16, 2009 Aruba, Dutch Antiles. [3] A.H. Phan and A. Cichocki : " Block Decomposition for Very Large-Scale Nonnegative Tensor Factorization", The Third International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP-2009, Dec.

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13-16, 2009 Aruba. [4] A.H. Phan and A. Cichocki : "Advances in PARAFAC Using Parallel Block Decomposition", 16th International Conference on Neural Information Processing. ICONIP-2009, Bangkok, Thailand, December 1-5, 2009. [5] A.H. Phan and A. Cichocki : "Local Learning Rules for Nonnegative Tucker Decomposition", 16th International Conference on Neural Information Processing. ICONIP-2009, Bangkok, Thailand, December 2-5, 2009. [6] A. Cichocki, R. Zdunek, S. Choi, R. Plemmons and S. Amari, ”Non-negative Tensor Factorization using Alpha and Beta Divergences”, in Proceedings of the 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP-2007, vol. III, April 1520, 2007, Honolulu, Hawaii, U.S.A., pp. 13931396. [7] J. Dauwels, T.M. Rutkowski, F. Vialatte, and A. Cichocki, ”On the synchrony of empirical mode decompositions with application to electroencephalography,” in Proceedings of the 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2008, (Las Vegas, Nevada, U.S.A.), IEEE, March 30 - April 4, 2008. [8] Y.-D. Kim, A. Cichocki, and S. Choi, ”Nonnegative Tucker decomposition with alpha-divergence,” in Proceedings of the 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2008, (Las Vegas, Nevada, U.S.A.), IEEE, March 30 - April 4, 2008. [9] A. Cichocki, S. Amari, R. Zdunek, R. Kompass, G. Hori and Z. He, ”Extended SMART Algorithms for Non-Negative Matrix Factorization”, Lecture Notes on Artificial Intelligence (LNAI), Springer, Eighth International Conference on Artificial Intelligence and Soft Computing, ICAISC, Zakopane, Poland, 25-29 June, 2006. [10] A. Cichocki, R. Zdunek, and S. Amari, ”Csiszar’s Divergences for Non-Negative Matrix Factorization: Family of New Algorithms”, 6th International Conference on Independent Component Analysis and Blind Signal Separation, Charleston SC, USA, March 5-8, 2006, Springer LNCS 3889, pp. 32-39. [11] A. Cichocki, R. Zdunek, and S. Amari, ”New Algorithms for Non-Negative Matrix Factorization in Applications to Blind Source Separation”, 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2006, May 14-19, 2006, Toulouse, France. [12] A. Cichocki and R. Zdunek, ”Multilayer Nonnegative Matrix Factorization Using Projected Gradient Approaches”, ICONIP, October 2006, Hong Kong). [13] A. Funase, Y. Tohru, M. Mouri, A.K. Barros, A. Cichocki, and I. Takumi, ”Analysis on EEG Signals in Visually and Auditory Guided Saccade Task by FICAR”, 6th Inter-

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national Conference on Independent Component Analysis and Blind Signal Separation, Charleston SC, USA, March 5-8, 2006, Springer LNCS 3889, pp. 438-445. [14] Z. He, and A. Cichocki, ”K-Subspace Clustering and its Application in Sparse Component Analysis”, The 14th European Symposium on Artificial Neural Networks, ESANN-2006 Bruges (Belgium), April 26-28, 2006. [15] Z. He, and A. Cichocki, ”K-EVD Clustering and its Applications to Sparse Component Analysis”, 6th International Conference on Independent Component Analysis and Blind Signal Separation, Charleston SC, USA, March 5-8, 2006, Springer LNCS 3889, pp. 90-97. [11] Y. Li and Z. Chen, A. Cichocki, and T.M. Rutkowski, ”Constrained Non-Negative Matrix Factorization Method for EEG Analysis in Early Detection of Alzheimer’s Disease”, 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2006, May 14-19, 2006, Toulouse, France. [12] M. Mouri, A. Funase, A. Cichocki, I. Takumi, H. Yasukawa, and M. Hata, ”Global Noise Elimination from ELF Band Electromagnetic Signals by Independent Component Analysis”, 6th International Conference on Independent Component Analysis and Blind Signal Separation, Charleston SC, USA, March 5-8, 2006, Springer LNCS 3889, pp. 384-391. [13] Y. Washizawa, and A. Cichocki, ”On Line K-Plane Clustering Learning Algorithm for Sparse Component Analysis”, 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP2006, May 14-19, 2006, Toulouse, France. [14] R. Zdunek, and A. Cichocki, ”Non-Negative Matrix Factorization with Quasi-Newton Optimization”, 8th International Conference on Artificial Intelligence and Soft Computing, ICAISC, Zakopane, Poland, 25-29 June, 2006, Springer Lectures Notes in Artificial Intelligence, Vol. 4029, pp. 870-879. [15] A. Cichocki: ”Blind source separation: New tools for extraction of source signals and denoising”, in Proceedings of SPIE, Vol. 5818, pp. 11-24, Special Session: Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks III, edited by Harold H. Szu, (SPIE, Bellingham, WA, 2005). [16] P. Georgiev, F. Theis, A. Cichocki, H. Bakardjian, ”Sparse Component Analysis: A New Tools for Data Mining”, In the book. Data Mining in Biomedicine, P.M. Pardalos, V. Boginski and A. Vazacopoulos (eds.) Springer, 2005. [17] Y. Li, A. Cichocki, and J. Qin: ”Blind identification and deconvolution for noisy two-input two-output channels”, Lecture Notes in Computer Science, J. Wang, X. Liao, and Z. Yi (Eds.): ISNN 2005, LNCS 3497, pp. 502507, 2005, Springer-Verlag Berlin

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Heidelberg 2005. [18] W. Liu, D. P. Mandic, and A. Cichocki: ”A class of blind source separation algorithms based on a linear prediction”. in Proceedings of International Symposium Circuits and Systems, ISCAS-2005, Kobe, May 2005, pp 3599-3602. [19] J. Qin, Y. Li, and A. Cichocki: ”ICA and committee machine-based algorithm for cursor control in a BCI system”, Lecture Notes in Computer Science, J. Wang, X. Liao, and Z. Yi (Eds.): ISNN 2005, LNCS 3496, pp. 973978, 2005, Springer-Verlag Berlin Heidelberg 2005. [20] F. Vialatte, A. Cichocki, G. Dreyfus, T. Musha, T. Rutkowski, and R. Gervais, ”Blind source separation and sparse bump modeling of time frequency representation of EEG signals: New tools for early detection of Alzheimer’s disease”, Proceedings of the 2005 IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, MLSP2005, Mystic CT, USA, September 2005, pp. 27-32 [21] F. Vialatte, A. Cichocki, G. Dreyfus, T. Musha, S. L. Shishkin, and R. Gervais: ”Early Diagnosis of Alzheimer’s Disease by Blind Source Separation, Time Frequency Representation, and Bump Modeling of EEG Signals” in the book: Artificial Neural Networks: Biological Inspirations ICANN 2005, 15th International Conference Warsaw, Poland, September 11-15, 2005 Proceedings, Part I , Eds. W. Duch, J. Kacprzyk, E. Oja, and S. Zadrozny, Springer, LNCS 3696, 2005, pp. 683-692. [22] A. Cichocki, Y. Li, P. Georgiev and S. Amari: ”Beyond ICA: Robust sparse signal representations”, IEEE International Symposium on Circuits and Systems (ISCAS 2004), Vancouver, Canada, May 23-26, 2004. [23] P. Georgiev and A. Cichocki: ”Sparse component analysis of overcomplete mixtures by improved basis pursuit method”, IEEE International Symposium on Circuits and Systems (ISCAS 2004), Vancouver, Canada, May 23-26, 2004. [24] P. Georgiev, F. Theis and A. Cichocki: ”Blind Source Separation and Sparse Component Analysis of overcomplete mixtures”, International Conference on Acoustics and Statistical Signal Processing (ICASSP 2004), Montreal, Canada, May 17-21, 2004. [25] F. Theis, P. Georgiev and A. Cichocki: ”Robust overcomplete matrix recovery for sparse sources using a generalized Hough transform”, 12-th European Symposium on Artificial Neural Networks, ESANN 2004, Bruges, Belgium, April 28-30, 2004. [26] T. Tanaka and A. Cichocki: ”Subband decomposition independent component analysis and new performance criteria”, International Conference on Acoustics and Statistical Signal Processing (ICASSP 2004), Montreal, Canada, May 17-21, 2004. [27] A. Cichocki: ”Semi-blind extraction and decomposition of multi-sensory signals: recent trends and perspective”, Proceedings of XII. International Symposium on

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Theoretical Electrical Engineering (ISTET03)”, ISTET, Electrotechnical Institute in Warsaw and others, Warsaw, 1-20 (2003). [28] S.A Cruces-Alvarez and A. Cichocki : ”A projection pursuit methodology for blind signal extraction”, Proc. of 13th international meeting of the Psychometric society, (IMPS2003), Cagliari, Italy, 2003. [29] H. Bakardjian and A. Cichocki: ”Classification of fast imagined motion responses for a human-computer interface”, Proceedings of the 42nd Annual Conference of Japanese Society for Medical and Biological Engineering, Sapporo, June 3-5, 2003, p.462. [30] Georgiev P. and Cichocki P., ”Sparseness theorems and sparse representation of signals”, to appear in Proceedings of RIMS (Research Institute of Mathematical Sciences) Symposium on ”Nonlinear Analysis and Convex Analysis” Kyoto University, Sep. 16–18, 2003. [31] A.K. Barros, A. Cichocki, and N. Ohnishi: ”Neural coding by temporal and spatial correlations”, International Meeting of the Psychometric Society (IMPS-2001), Springer, Tokyo, 673-680 (2003). [32] Y. Li, A. Cichocki and S. Amari: Sparse component analysis for blind source separation with less sensors than sources, Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation April 1 4, 2003, Nara, Japan, pp. 89-95. [33] J. Karvanen and A. Cichocki: Measuring sparseness of noisy signals, Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation April 1 4, 2003, Nara, Japan, pp. 125-131. [34] T. Hoya, A. Kardec Barros, T. Rutkowski and A. Cichocki: Speech extraction based upon a combined subband Independent Component Analysis and neural memory, Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation April 1 4, 2003, Nara, Japan, 355-361. [35] S. A. Cruces-Alvarez and A. Cichocki: Globally convergent Newton algorithms for blind decorrelation, Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation, April 1 4, 2003, Nara, Japan, 421-427. [36] S. A. Cruces-Alvarez and A. Cichocki: Combining blind Source extraction with joint approximate diagonalization: Thin Algorithms for ICA , Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation, April 14, 2003, Nara, Japan, 463-469. [37] T. Hoya, A. Cichocki, T. Tanaka, T. Murakami, J.A. Chambers: A Combined

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Cascading Subspace and Adaptive Signal Enhancement Method for Stereophonic Noise Reduction, Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation, April 1 4, 2003, Nara, Japan, pp. 573-579. [38] D. Mandic and A. Cichocki: An online algorithm for blind extraction of sources with different dynamical structures, Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation, April 1 4, 2003, Nara, Japan, pp. 645-651. [39] D. Mandic A. Cichocki and U. Manmontri, U.: ”An on-line algorithm for blind source extraction based on nonlinear prediction approach”, 2003 IEEE International Workshop on Neural Networks for Signal Processing, IEEE, New York, 429-438 (2003). [40] A. Funase, A. K. Barros, S. Okuma, T. Yagi and A. Cichocki: Research of saccade- related EEG: Comparison of ensemble averaging method and Independent Component Analysis, Proc. of Fourth International Symposium on Independent Component Analysis and Blind Signal Separation, April 1 4, 2003, Nara, Japan, 867-973. [41] Y. Li, A. Cichocki and L. Zhang: Blind deconvolution for binary sources: A grouping decision Approach, IEEE International Conference on Acoustics, Speech and Signal Processing, Hong Kong, April 7-9, 2003. [42] A. Cichocki, T. Rutkowski and K. Siwek: Blind signal extraction of signals with specified frequency band, International Workshop on Neural Network for Signal Processing, Martigny, Switzerland, Sept. 4-7, 2002, pp. 515-524. [43] A. Cichocki and P. Georgiev: Blind identification problems with constraints, International Workshop on Neural Network for Signal Processing, Martigny, Switzerland, Sept. 4-7, 2002, pp. 535-544. [44] S. Choi, A. Cichocki and S. Amari: Natural gradient learning for second-order nonstationary source separation, in Proc. IJCNN 2002, pp. 654-658, Honolulu, Hawaii, May 12-17, 2002. [45] J. C. Rajapakse, A. Cichocki, and D. Sanchez: ICA in Brain Imaging: fMRI, EEG, and MEG, International Conference on Neural Information Processing, (ICONIP2002), Nov. 2002, Singapore, pp. 404-412. [46] P. Georgiev and A. Cichocki: Robust blind source separation and dispersing algorithms, Proceedings of the International Conference on Acoustics Speech and Signal Processing, Orlando, Florida, May 13-17, 2002. [47] A. Bousbia-Salah, A. Belouchrani and A. Cichocki: Application of time-frequency distributions to the independent component analysis of ECG signals, Proceedings of Sixth International Symposium on Signal Processing and its Applications, Kuala-

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Lumpur, August 2001, pp.238-241. [48] J. Cao, N. Murata, S. Amari, A. Cichocki and T. Takeda: A robust ICA approach for unaveraged single-trial auditory evoked fields data decomposition, 3rd International Conference on Independent Component Analysis and Signal Separation, San Diego California, December 9-13, 2001, pp. 445-450. [49] S. Choi, A. Cichocki and Y. Deville: Differential decorrelation for non-stationary source separation, 3rd International Conference on Independent Component Analysis and Signal Separation, San Diego California, December 9-13, 2001, pp. 319-322. [50] S. Choi and A. Cichocki: Correlation matching approach to source separation in the presence of spatially correlated noise, Proceedings of International Symposium on Signal Processing and Applications (IEEE ISSPA2001), Kuala-Lumpur, Malaysia, August 13-16, 2001. [51] S. Choi, A. Cichocki, L. Zhang and S. Amari: Approximate maximum likelihood source separation using the natural gradient, Proceedings of the 2001 IEEE Third Workshop on Signal Processing Advances in Wireless Communications (SPAWC’01), March’2001, pp. 235-238. [52] S. Choi, A. Cichocki and A. Belouchrani: Blind separation of second-order nonstationary and temporally colored sources, Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, Singapore, August 2001, pp. 444-447. [53] A. Cichocki and A. Belouchrani: Sources separation of temporally correlated sources from noisy data using bank of band-pass filters, 3rd International Conference on Independent Component Analysis and Signal Separation, San Diego California, December 9-13, 2001, pp. 173-178. [54] A. Cichocki, R.R. Gharieb and N. Mourad: Extraction of superimposed evoked potentials by combination of independent component analysis and cumulant-based matched filtering, Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, Singapore, August 2001, pp.237-240. [55] A. Cichocki, R. R. Gharieb and T. Hoya: Efficient extraction of evoked potentials by combination of Wiener filtering and subspace methods, IEEE Int. Conf. Acoust., Speech, Signal Processing, ICASSP-2001, May 2001, Utah, USA, Vol. 5, pp. 3117-3120. [56] S. Cruces, A. Cichocki, S-I. Amari: Criteria for the simultaneous blind extraction of arbitrary groups of sources, 3rd International Conference on Independent Component Analysis and Signal Separation, San Diego California, December 9-13, 2001, pp. 740-

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745. [57] P. Georgiev and A. Cichocki: Multichannel blind deconvolution of colored signals via eigenvalue decomposition, Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, Singapore, August 2001, pp. 273-276. [58] P. Georgiev and A. Cichocki: Blind source separation via symmetric eigenvalue decomposition, Proceedings of Sixth International Symposium on Signal Processing and its Applications, Kuala-Lumpur, August 2001, pp.17-20. [59] P. Georgiev, A. Cichocki and S. Amari: On some extensions of the natural gradient algorithm, 3rd International Conference on Independent Component Analysis and Signal Separation, San Diego California, December 9-13, 2001, pp. 581-585. [60] P. G. Georgiev, A. Cichocki and S. Amari: Nonlinear dynamical system generalizing the natural gradient algorithm, Proceedings of 2001 International Symposium on Nonlinear Theory and its Applications, Miyagi, Japan, 2001, pp. 391-394. [61] R. R. Gharieb and A. Cichocki: On-line EEG classification and sleep spindles detection using an adaptive recursive bandpass filter, IEEE Int. Conf. Acoust., Speech, Signal Processing, ICASSP-2001, May 2001, Utah, USA, Vol. 2, pp. 1061-1064. [62] Y. Li, A. Cichocki and L. Zhang: Blind separation of digital sources, Neural Information Processing (ICONIP 2001 Proceedings), Fudan Univ. Press, Shanghai 2001, pp. 1018-1022. [63] N. Mourad, R. R. Gharieb and A. Cichocki: Extended flexible independent component analysis, Proceedings of the 1st IEEE Symposium on Signal Processing and Information theory (ISSIT-2001), December 28-30, 2001, Cairo, Egypt, pp. 305-310. [64] T. Rutkowski, A. Cichocki and A. K. Barros: Speech enhancement from interfering sounds using CASA techniques and blind source separation, 3rd International Conference on Independent Component Analysis and Signal Separation, San Diego California, December 9-13, 2001, pp. 728-733. [65] L. Zhang, A. Cichocki: Feature extraction and blind separation of convolutive signals, Neural Information Processing (ICONIP’2001 Proceedings), Fudan Univ. Press, Shanghai, pp. 789-794. [66] L. Zhang, A. Cichocki: Sparse representation and blind deconvolution of dynamical systems, 3rd International Conference on Independent Component Analysis and Signal Separation, San Diego California, December 9-13, 2001, pp. 284-289. [67] A.K. Barros, H. Kawahara, A. Cichocki, S. Kojita, T. Rutkowski, M. Kawamoto and N. Ohnishi: Enhancement of a speech signal embedded in Noisy environment using

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two microphones, Proceedings of the Second International Workshop on ICA and BSS, ICA’2000, Helsinki, Finland,19-22 June, 2000, pp. 423-428. [68] J. Cao and A. Cichocki: Independent features extraction from multivariable time series biomedical recordings. Proceedings of the IEEE-EMBS Asia-Pacific Conference on Biomedical Engineering 2000 , pp. 185-186. [69] J. Cao, N. Murata, S. Amari, A. Cichocki, H. Endo, N. Harada and T. Taketa: Independent features analysis for MEG recorded auditory evoked fields task data. Proc. of 2000 International Symposium on Nonlinear Theory and its Applications (NOLTA), Dresden, Germany, September 2000, pp. 257-260. [70] S. Choi, A. Cichocki and S. Amari: Local stability analysis of flexible independent component analysis algorithm, Proceedings of 2000 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2000), Istanbul, Turkey, June 5-9, 2000, pp. 3426-3429. [71] S. Choi and A. Cichocki: Blind separation of non-stationary and temporally correlated sources from noisy mixtures, IEEE Workshop on Neural Networks for Signal Processing, NNSP’2000, Sydney, Australia, December 11-13, 2000, pp. 405-414. [72] A. Cichocki: Semi blind processing: models and learning algorithms. 7th International Conference on Neural Information Processing, ICONIP-2000, pp. 1353-1358. [73] A. Cichocki: Independent component analysis for classification and independent cancellation in multisensory biomedical data. International Center of Biocybernetics World Health Organization, Center for Research and Training in Biocybernetics and Biomedical Engineering, Warsaw, Poland, Jun. 2000, pp. 29-39. [74] A. Cichocki, T. Rutkowski, A. K. Barros and S.-H. Oh: Blind extraction of temporally correlated but statistically dependent acoustic signals, IEEE Workshop on Neural Networks for Signal Processing, NNSP ’2000, Sydney, Australia, December 11-13, 2000, pp. 455-464. [75] A. Cichocki and S. Vorobyov: Application of ICA for automatic noise and interference Cancellation in Multi-sensory Biomedical Signals, Proceedings of the Second International Workshop on ICA and BSS, ICA’2000, Helsinki, Finland, June 19-22, 2000, pp. 621-626. [76] S. Cruces, L. Castedo and A. Cichocki: Novel blind source separation algorithms using cumulant. 2000 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP-2000), Istanbul, Turkey, Jun. 2000, pp. 3152-3155. [77] S. Cruces, A. Cichocki and L. Castedo: Blind source extraction in Gaussian noise, Proceedings of the Second International Workshop on ICA and BSS, ICA’2000,

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Helsinki, Finland, June 19-22, 2000, pp. 63-68. [78] R. R. Gharieb, Y. Horita, T. Murai and A. Cichocki: Unity-gain cumulant-based adaptive line enhancer. Proceedings of the tenth IEEE workshop on Statistical signal and array processing, August 14-16, 2000, Pocono Manor, Pennsylvania, USA, pp. 626-630. [79] R. R. Gharieb, A. Cichocki and S.F. Filipowicz: Adaptive detection and extraction of sparse signals embedded in colored Gaussian noise using higher order statistics. Proceedings of the tenth IEEE workshop on statistical signal and array processing, August 14-16, 2000, Pocono Manor, Pennsylvania, USA, pp. 631-634. [80] S. Oh, A. Cichocki, S. Choi, S. Amari and S.-Y. Lee: Comparison of ICA/BSS algorithms for noisy data. 7th International Conference on Neural Information Processing, ICONIP-2000, pp. 1192-1197. [81] T. Rutkowski, A. Cichocki and A. K. Barros: Speech enhancement using adaptive filters and Independent Component Analysis approach, International Conference on Artificial Intelligence in Science and Technology, AISAT’2000, Hobart, Tasmania, 17-20 December, 2000, pp. 191-196. [82] S. A. Vorobyov and A. Cichocki: Self-excited oscillations and period doubling condition in Hopfield neural network.2000 2nd International Conference, Control of Oscillations and Chaos, 2000, pp. 197-200. [83] L. Zhang, A. Cichocki and S. Amari: Estimating function approach to multichannel blind deconvolution, Proc. of IEEE Asia Pacific Conference on Circuits and Systems, Tianjin, China, 2000, pp. 587-590. [84] L. Zhang and A. Cichocki: Natural gradient approach to blind deconvolution of dynamic systems, Proceedings of the Second International Workshop on ICA and BSS, ICA’2000, Helsinki, Finland, June 19-22, 2000, pp. 27-32. [85] L. Zhang, A. Cichocki and S. Amari: Kalman filter and state-space approach to multi-channel blind deconvolution, IEEE Workshop on Neural Networks for Signal Processing, NNSP ’2000, Sydney, Australia, December 11-13, 2000, pp. 425-434. [86] A. D. Back and A. Cichocki: Input variable selection using independent component analysis and higher order statistics, Proceeding of the First International Workshop on Independent Component Analysis and Signal Separation, ICA’99, Aussois, France, January 11-15, 1999, pp. 203-208. [87] J. Cao, N. Murata, S. Amari, A. Cichocki, T. Takata, H. Endo and N. Harada: Independent Source separation and localization of single-trial magneto-encephalographic data, Proceeding of 1999 International Symposium on Nonlinear Theory and its Applications (NOLTA’99), Hawaii, U.S.A., November 28-December 2,

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1999, pp. 719-722. [88] S. Choi, S. Amari, A. Cichocki and R. Liu: Natural gradient learning with a nonholonomic constraint for blind deconvolution of multiple channels, Processing of the 1st in International Workshop on Independent Component Analysis and Blind Signal Separation (ICA’99), Aussois, France, January 11-15, 1999, pp. 371-376. [89] S. Choi and A. Cichocki: A hybrid learning approach to blind deconvolution of MIMO systems, Processing IEEE Signal ProcessingWorkshop on Higher-Order Statistics (HOS’99), Caesarea, Israel, IEEE Computer Society, Los Alamitos, June 14-16, 1999, pp. 292-295. [90] S. Choi, A. Cichocki and S. Amari: Two spatio-temporal deceleration learning algorithms and their application to multichannel blind deconvolution, ICASSP’99, Phoenix, Arizona, March 15-19, 1999, pp. 1085-1088. [91] S. Choi, A. Cichocki and S. Amari: Fetal electrocardiogram data analysis via flexible independent component analysis, The 4th Asia Pacific Conference on Medical and Biological Engineering (APCMBE ’99), September 12-15, 1999. [92] S. Choi, Y. Lyu, F. Berthommier, H. Glotin and A. Cichocki: Blind separation of delayed and superimposed acoustic sources: Learning algorithm and experimental study, Proceedings of International Conference on Speech Processing (ICSP ’99), Seoul, Korea, August 18-20, 1999, pp. 109-114. [93] A. Cichocki and A. K. Barros: Robust batch algorithm for sequential blind extraction of noisy biomedical signals, 5th International Symposium on Signal Processing and its Applications (ISSPA’99), Brisbane, Queensland, Australia, Vol. 1, August 1999, pp. 363-366. [94] A. Cichocki, S. A. Vorobyov and T. Rutkowski: Nonlinear interference cancellation using neural networks, Proceeding of 1999 International Symposium on Nonlinear Theory and its Applications (NOLTA ’99), Hawaii, U.S.A, November 28-December 2, 1999, pp. 875-887. [95] A. Cichocki, L. Zhang, S. Choi and S. Amari: Nonlinear dynamic independent component analysis using state-space and neural network models, Proceeding of the First International Workshop on Independent Component Analysis and Signal Separation (ICA ’99), Aussois, France, January 11-15, 1999, pp. 99-104. [96] A. Cichocki and L. Zhang: Adaptive multichannel blind deconvolution using state-space models, Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics (HOS ’99), Ceasarea, Israel, June 1999, pp. 296-299. [97] A. Cichocki, L. Zhang and T. Rutkowski: Blind separation and filtering using state space models, Proceedings of the 1999 IEEE International Symposium on Circuits and

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Systems (ISCAS’99), Orlando, Florida, U.S..A., Vol. V, May 30 - June 2, 1999, pp. 78-81. [98] S. Cruces, L. Castedo and A. Cichocki: An iterative inversion method for blind source separation, Proc. of the First International Workshop on Independent Component Analysis and Signal Separation (ICA’99), Aussois, France, January 11-15, 1999, pp. 307-312. [99] L. Zhang, S. Amari and A. Cichocki: Natural gradient approach to blind separation of over- and under-complete mixtures, Proceeding of the 1st International Workshop on Independent Component Analysis and Signal Separation (ICA’99), Aussois, France, January 11-15, 1999, pp. 455-460. [100] L. Zhang, S. Amari and A. Cichocki: Semiparametric approach for blind deconvolution of nonminimum phase systems, Neural Information Processing Systems- Natural and Synthetic (NIPS’99), (NIPS Foundation), Denver, U.S.A., December 1999. [101] L. Zhang, A. Cichocki and S. Amari: Geometrical structures of FIR manifold and their application to multichannel blind deconvolution, Proceedings of NNSP’99, Madison, U.S.A., edited by Y. Hu, J. Larsen, E. Wilson and S. Gouglas., The Institute of Electrical and Electronics Engineers, Inc., New York, U.S.A, August 1999, pp. 303-314. [102] L. Zhang, A. Cichocki and S. Amari: Multichannel blind deconvolution of nonminimum phase systems using information back-propagation, ICONIP’99, Perth, Australia, IEEE, edited by T. Gedeon, P. Wong, S. Halgamuge, N.Kasabov, D. Nauck, K. Fukushima, Piscataway, U.S.A., November 1999, pp. 210-216. [103] L. Zhang, A. Cichocki and S. Amari: Semiparametric approach to blind separation of dynamical systems, Proceeding of 1999 International Symposium on Nonlinear Theory and its Applications, NOLTA’99, Hawaii, U.S.A., edited by H. Takakubo, T. Kohda, L. Trajkovic, November 28-December 2, 1999, pp. 707-710. [104] L. Zhang, A. Cichocki, J. Cao and S. Amari: Semiparametric approach to blind deconvolution, Technical Report of IEICE, The Institute of Electronics, Information & Communication Engineers, NC ’99-25, Japan, June 1999, pp. 99-106. [105] T. Zhang, A. Cichocki, E. F. Kelly, S. E. Folger and P. J. Durka: Independent component analysis (ICA) of vibrotactile driving responses, UCL Meeting of the Physiological Society, University College London, London, U.K., April 1999. [106] S. Amari, S.C. Douglas and A. Cichocki: Information geometry of blind source deconvolution, presented at Mathematical Theory of Networks and Systems, Padova, Italy, July 1998.

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[107] J. Cao, N. Murata, S. Amari, A. Cichocki and T. Takeda: MEG data analysis based on ICA approach with pre- and post-processing techniques, in Proceedings of 1998 International Symposium on Nonlinear Theory and its Applications (NOLTA-98), Vol. 1, Switzerland Sept. 1998, pp.287-290. [108] S. Choi and A. Cichocki: On-line sequential multichannel blind deconvolution, a deflation approach, DSP Workshop, Utah USA, 1998, 159-162. 27 [109] S. Choi, A. Cichocki and S. Amari: Flexible independent component analysis, in Neural Networks for Signal Processing VIII, IEEE Press, N.Y. 1998, Proc. of the 1998 IEEE Workshop on NNSP Cambridge, UK, August 1998, pp. 83-92. [110] S. Choi, A. Cichocki and S. Amari: Blind equalization of SIMO channels via spatiotemporal anti-Hebbian learning rule, in Neural Networks for Signal Processing VIII, IEEE Press, N.Y. 1998, Proc. of the 1998 IEEE Workshop on NNSP Cambridge, UK, August 1998, pp. 93-102. [111] A. Cichocki and J. Cao: A self-adaptive neural network for on-line blind separation of convolved sources, Proc. of III Int. Workshop- Advances in Signal Processing for NDE of Materials, in the book Topics on Non-destructive Evaluation Series, Eds. B. B. Djordjevic and H. D. Reis, The American Society for Non-destructive Evaluation Testing, Inc. Quebeck , 1998, pp. 207-212. [112] A. Cichocki, S. Douglas, S. Amari and P. Mierzejewski: Independent component analysis for noisy data, Proc. of International Workshop on Independence and Artificial Neural Networks, Tenerife, Feb. 9 - 10, 1998, pp. 52-58. [113] A. Cichocki, I. Sabala and S. Amari: Intelligent neural networks for blind signal separation with unknown number of sources, Proc. of Conf. Engineering of Intelligent Systems, ESI-98 Tenerife, Feb. 11-13, 1998, pp. 148-154. [114] A. Cichocki, L. Zhang and S. Amari: Semi-blind and state-space approaches to nonlinear dynamic independent component analysis, in Proceedings of 1998 International Symposium on Nonlinear Theory and its Applications (NOLTA-98), Vol. 1, Crans-Montana, Switzerland, Sept. 1998, pp.291-294. [115] A. Cichocki and L. Zhang: Two-stage blind deconvolution using state-space models (invited paper), Proceedings of the Fifth International Conference on Neural Information Processing (ICONIP’98), Kitakyushu, Japan, Oct. 21-23, 1998, pp. 729-732. [116] S. Cruces, A. Cichocki and L. Castedo: An unified perspective of blind source separation algorithms, Proceedings of the Learning’98 , Madrid (Spain), September 1998, (ISBN: 84-89315-11-6). [117] S.C. Douglas and A. Cichocki: Adaptive step size techniques for decorrelation

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and blind source separation, Proc. 32nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, vol. 2, November 1998, pp. 191-1195. [118] I. Sabala, A. Cichocki and S. Amari: Relationships between instantaneous blind source separation and multichannel blind deconvolution, Proc. Int. Joint Conference on Neural Networks, Alaska USA, May 1998, pp.148-152. [119] L. Zhang and A. Cichocki: Blind deconvolution/equalization using state-space models, in Neural Networks for Signal Processing VIII, IEEE Press, N.Y. 1998, Proceedings of the 1998 IEEE Workshop on Neural Networks for Signal Processing (NNSP’98), Cambridge, UK, August 31- September 2, 1998, pp. 123-131. [120] L. Zhang and A. Cichocki: Blind separation/deconvolution of sources using canonical stable state-space models, Proceeding of the 1998 international Symposium on Nonlinear 28 Theory and its Applications (NOLTA’98), Crans-Montana, Sept, 14-17, 1998, pp. 927-930. [121] L. Zhang and A. Cichocki: Information backpropagation learning algorithm for blind dynamic separation, Proceeding of IASTED International Conference Signal and Image Processing (SIP’98), October 28-31, 1998, Las Vegas, USA, pp.3-7. [122] S. Choi, A. Cichocki and S. Amari: Adaptive blind deconvolution and equalization with self-adaptive nonlinearities: An information-theoretic approach, in Progress in Connectionist-based Information Systems, N. Kasabov, R. Kozma, K. Ko, R. O’Shea, T. Gedeon, eds, vol. 1, 1997, pp. 641-644. [123] S. Choi and A. Cichocki: Blind signal deconvolution by spatio-temporal decorrelation and demixing, in Neural Networks for Signal Processing 7, J. Principe, L. Gile, N.Morgan and E. Wilson, eds, 1997, pp. 426-435. [124] S. Choi, S. Amari and A. Cichocki: Natural gradient learning algorithms for decorrelation, in Progress in Connectionist-based Information Systems, N. Kasabov, R. Kozma, K. Ko, R. O’shea, T. Gedeon, eds., vol. 1, 1997, pp. 645-648. [125] S. Amari, S.C. Douglas, A. Cichocki and H.H. Yang: Multichannel blind deconvolution and equalization using the natural gradient, Proc. of IEEE International Workshop on Wireless Communication, Paris April 1997, pp. 101-104. [126] S. Amari, T. Chen and A. Cichocki: Non-holonomic constraints in learning blind source separation, Progress in Connectionist-Based Information Systems, Eds. N. Kasabov, ICONIP-97, New Zealand, Springer Nov. 1997, Vol.I pp. 633-636. [127] S. Amari, S. Douglas, A. Cichocki and H.H. Yang: Novel on-line algorithms for blind deconvolution using natural gradient approach, Proc. of 11th IFAC symposium on System Identification, SYSID-97 Kitakyushu City, Japan, July 1997, pp. 1057-1062. [128] A.D. Back and A.C. Cichocki: Blind source separation and deconvolution of fast

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sampled signals, Progress in Connectionist-Based Information Systems, Eds. N. Kasabov, ICONIP-97, New Zealand, Springer Nov. 1997, Vol.I, pp. 637-641. [129] J. Cao and A. Cichocki: On-line blind sources separation algorithms for SIMO blind equalization systems, Proceedings of 12th Digital Signal Processing Symposium, Hiroshima, Japan, Nov. 1997, pp. 351-356. [130] J. Cao and A. Cichocki: Blind source separation algorithm based on 4th-order self-and cross-cumulants criterion applied for EEG data analysis, Proceedings of 1997 International Symposium on Nonlinear Theory and its Applications (NOLTA-97), Vol. 2, Hawaii, U.S.A. (Dec. 1997), pp. 1005-1008. [131] S. Choi and A. Cichocki: Blind signal deconvolution by spatio-temporal decorrelation and demixing, Neural Networks for Signal Processing VII, ed. by J. Principe, L. Gile, N. Morgan and E. Wilson, 1997, pp. 426-435. [132] S. Choi and A. Cichocki: A linear feedforward neural network with lateral feedback connections for blind source separation, IEEE Signal Processing Workshop on Higher-order Statistics, Banff, Canada, 21-23 July 1997, pp. 349-353. [133] S. Choi and A. Cichocki: Adaptive blind separation of speech signals: Cocktail party problem, International Conference on Speech Processing (ICSP’97), Seoul, Korea, 26-28 August 1997, pp. 617-622. [134] S. Choi, S. Amari and A, Cichocki: Natural gradient learning algorithms for decorrelation, Progress in Connectionist-Based Information Systems (Proceedings of the 1997 International Conference on Neural Information Processing) (ICONIP’97), Dunedin, New Zealand, Vol. 1, November 1997, pp. 645-648. [135] S. Choi, A. Cichocki and S. Amari: Adaptive blind deconvolution and equalization with self-adaptive nonlinearities: An information-theoretic approach, Progress in Connectionist-Based Information Systems (Proceedings of the 1997 International Conference on Neural Information Processing) (ICONIP’97), Dunedin, New Zealand, Vol. 1, November 1997, pp. 641-644. [136] A. Cichocki, J. Cao and I. Sabala: On-line adaptive algorithms for blind equalization of multi-channel systems, Progress in Connectionist-Based Information Systems, Eds. N. Kasabov, Springer, ICONIP-97, New Zealand, Nov. 1997, pp. 649-652. [137] A. Cichocki: Blind separation and extraction of source signals - recent results and open problems, Proc. of the 4-th Annual Conference of the Institute of Systems, Control and Information Engineers, ISCIIE, Osaka, May 21-23 1997, pp. 43-48. [138] A. Cichocki, I. Sabala, S. Choi, B. Orsier and R. Szupiluk: Self adaptive indepen- dent component analysis for sub-Gaussian and super-Gaussian mixtures with unknown

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number of sources and additive noise, Proceedings of 1997 International Symposium on Nonlinear Theory and its Applications (NOLTA-97), Vol. 2, Hawaii, U.S.A., Dec. 1997, pp. 731-734. [139] A. Cichocki, R. Thawonmas and S. Amari: Dual cascade networks for blind signal extraction, Proc. the 1997 International Conference on Neural Networks (ICNN’97), Houston, Vol. 4, 1997, pp. 2135-2140. [140] A. Cichocki, B. Orsier, A.D. Back and S. Amari: On-line adaptive algorithms in non stationary environments using a modified conjugate gradient approach, in Proc. of IEEE Workshop on Neural Networks for Signal Processing, N.Y. Press, Sept. 1997, pp. 316-325. [141] T. Cholewo, J.M. Zurada and A. Cichocki: Exact gradient calculation in Gamma neural networks, Proc. of the 1997 International Symposium on Nonlinear Theory and Applications, Honolulu, Hawaii, November 29-December 2, 1997, vol.2, pp. 767-770. [142] S.C. Douglas, A. Cichocki and S. Amari: Quasi-Newton filtered-error and filtered-regressor algorithms for adaptive equalization and deconvolution, presented at IEEE Workshop Signal Proc. Adv. Wireless Comm., Paris, April 1997, pp. 109-112. [143] S.C. Douglas, A. Cichocki and S. Amari: Multichannel blind separation and deconvolution of sources with arbitrary distributions, in Neural Networks for Signal Processing, Proc. of the 1997 IEEE Workshop (NNSP-97), Sept. 1997, N.Y. IEEE Press, pp. 436-445. [144] T. Lobos, A. Cichocki, P. Kostyla and Z. Waclawek: Adaptive on-line learning algorithm for robust estimation of parameters of noisy sinusoidal signals, Artificial neural networks - ICANN ’97. Proceedings of 7th International Conference, Wulfram Gerstner, Lausanne, Switzerland, October 8-10, 1997, Berlin Springer-Verlag 1997, ISSN 0302-9743, pp. 1193-1198. [145] S. Osowski, A. Majkowski and A. Cichocki: Robust PCA neural networks for random noise reduction of the data, Proc. 1977 Int. Conf. on Acoustic, Speech and Signal Processing (ICASSP-97), Munich, Germany 1997, pp. 3397 - 3400. [146] S. Osowski, A. Cichocki and L. Tran Hoai: Signal flow graphs in application to recurrent neural networks learning, Proc. of 1997 European Conference on Circuit Theory and Design (ECCTD-97), Budapest, Hungary, Sept. 1997, pp. 1092-1097. [147] R. Thawonmas and A. Cichocki: Blind extraction of source signals with specified stochastic features, in Proceedings of Int. Conference on Acoustic Speech and Signal Processing, ICASSP-97, Vol.4, pp. 3353-3357. [148] R. Thawonmas, S. Abe and A. Cichocki: A fuzzy function approximator based on

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partitioned hyperboxes, Joint Pacific Asian Conference on Expert Systems/Singapore International Conference on Intelligent Systems - PACES/SPICIS’97, Singapore, February, 1997, pp. 537-544. [149] S. Amari, A. Cichocki and H.H Yang: A new learning algorithm for blind signal separation, Advances in Neural Information Processing Systems 1995 (NIPS-95), vol. 8, MIT Press, Cambridge MA, 1996, 757-763. [150] M. Adachi, K. Aihara and A. Cichocki: Separation of mixed patterns by a chaotic neural network, International Symposium on Nonlinear Theory and its Applications - NOLTA’96, Proceedings. Research Society on NTA, IEICE, Japan, Oct. 1996, pp. 93-96. [151] A. Belouchrani, A. Cichocki and K. Abed Meraim: A Blind identification and separation technique via multi-layer neural networks, in Progress in Neural Information Processing - ICONIP’96, Proceedings, (Hong Kong Sept. 1996), Springer-Verlag Singapore Ltd, Vol. 2, pp. 1195-1200. [152] J. Cao, S. Amari and A. Cichocki: Self-scaling and self-adaptive neural networks for on-line nonlinear dynamical systems identification, Proceedings of 1996 International Symposium on Multi-Technology Information Processing (ISMIP-96), Taiwan, Dec. 1996, pp. 499-504. [153] J. Cao, A. Cichocki: A simplified architecture for nonlinear recurrent neural filter, Progress in Neural Information Processing - ICONIP’96, Proceedings, (Hong Kong, Sept. 1996), Springer-Verlag Singapore Ltd, 1996, Vol.1, pp. 514-519. [154] A. Cichocki, S. Amari and J. Cao: Blind separation of delayed and convolved signals with self-adaptive learning rate, Proc. 1996 IEEE International Symposium on Nonlinear Theory and its Applications, NOLTA-96, Kochi Japan, Oct. 7-9, 1996, pp. 229-232. [155] A. Cichocki, S. Amari and R. Thawonmas: Blind signal extraction using self-adaptive non-linear Hebbian learning rule, International Symposium on Nonlinear Theory and its Applications - NOLTA’96, Proceedings. Kochi Japan, Oct. 1996, pp. 377-380. [156] A. Cichocki, W. Kasprzak and S. Amari: Adaptive approach to blind source separation with cancellation of additive and convolutional noise, ICSP’96, 3rd Int. Conf. on Signal Processing, Proceedings, IEEE Press/PHEI Beijing, Vol. I, Sept. 1996, pp. 412-415. [157] A. Cichocki, W. Kasprzak and S. Amari: Neural network approach to blind separation and enhancement of images, in Signal Processing VIII. Theories and Applications., EURASIP/LINT Publ., Trieste, Italy, Vol.I, Sept. 1996, pp. 579-582.

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[158] A. Cichocki, A. Kasprzak, W. Skarbek: Adaptive learning algorithm for principal component analysis with partial data, Cybernetics and Systems 1996. 13-th European Meeting on Cybernetics and Systems Research, Austrian Society for Cybernetic Studies, Vienna, 1996, pp. 1014-1019. [159] A. Cichocki, R. Swiniarski and R. Bogner: Hierarchical neural network for robust PCA of complex-valued signals, Proc. of World Congress on Neural Networks, WCNN’96 -1996 Int. Neural Network Society Annual Meeting in San Diego, USA, September 1996, pp. 818-821. [160] A. Cichocki, S. Amari, M, Adachi and W. Kasprzak: Self-adaptive neural networks for blind separation of sources, Proc. of 1996 IEEE International Symposium on Circuit and Systems, Vol. 2, May 1996, pp. 157-160. [161] A. Cichocki, P. Kostyla, T. Lobos and Z.Waclawek: Adaptive neural networks for robust estimation of parameters of noisy harmonic signals, Signal Processing VIII. Theories and Applications (EUSIPCO-96), EURASIP/LINT Publ., Trieste, Italy, 1996, vol.I, pp. 220-223. [162] S.C. Douglas and A. Cichocki: Convergence analysis of local algorithms for blind signal processing, Neural Information Processing Systems Conf., Workshop on Blind Signal Processing, Denver, CO, December 2-7, 1996. [163] R. Foltyniewicz, A. Cichocki: Higher order neural networks with wavelets preprocessing for face recognition, World Congress on Neural Networks, WCNN’96 - 1996 Int. Neural Network Society Annual Meeting in San Diego, USA, Sep. 1996. Proceedings. INNS Press & Lawrence Erlbaum Associates Inc. Publ., Mahwah, NJ, pp. 919-922. [164] W. Kasprzak and A. Cichocki: Recurrent least squares learning for quasi-parallel principal component analysis, ESANN’96. Proceedings, D’facto Publ., Brussels, 1996, pp. 223-228. [165] W. Kasprzak and A. Cichocki: Hidden image separation from incomplete image mixtures by independent component analysis, 13th Int. Conf. on Pattern Recognition, ICPR’96, vol. II, IEEE Computer Society Press, Los Alamitos CA, August 1996, pp. 394-398. [166] A. Krzyzak and A. Cichocki: On the convergence of the recursive radial basis function networks, World Congress on Neural Networks, WCNN’96 - 1996 Int. Neural Network Society Annual Meeting in San Diego, USA, Sep. 1996. Proceedings. INNS Press &Lawrence Erlbaum Associates Inc. Publ., Mahwah, NJ, pp. 239-243. [167] M.J. Ogorzalek, Z. Galias and A. Cichocki: Study of noise influence on self-organization phenomena in chaotic neural networks, 1996 IEEE Int. Symposium on

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Circuits and Systems, ISCAS’96, Vol. 3, IEEE, Piscataway, NJ, 1996, pp. 87-91. [168] S. Osowski and A. Cichocki: SFG approach to the sensitivity determination of dynamic recurrent systems, World Congress on Neural Networks, WCNN’96 - 1996 Int. Neural Network Society Annual Meeting in San Diego, USA, Sep. 1996. Proceedings. INNS Press & Lawrence Erlbaum Associates Inc. Publ., Mahwah, NJ, pp. 256-259. [169] S. Osowski and A. Cichocki: Application of SFG in Learning Algorithms of Neural Networks, NICROSP’96, 1996 Int. Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing, Venice, Italy, August 1996, pp. 75-84. [170] S. Osowski and A. Cichocki and T.H. Linh: Learning in recurrent neural dynamic systems using signal flow graphs, Krajowa Konferencja Teorii Obwodow i Ukladow Elektronicznych (KKTOiUE), Karpacz, 1996, pp. 669-674. [171] S. Amari, A. Cichocki, H.H.Yang: A new learning algorithm for blind signal separation, Advances in Neural Information Processing Systems 1995 , vol.8, MIT Press, Cambridge MA, 1995, pp. 757-763. [172] A. Cichocki, R. Bogner, L. Moszczynski: Improved adaptive algorithms for blind separation of sources, Proceedings of Conference on Electronic Circuits and Systems, KK-TOiUE, Zakopane Poland, Oct. 1995, pp. 647-652. [173] W. Skarbek and A. Cichocki: Gray scale image representation by recurrent vector neural network, Int. Symposium on Nonlinear Theory and its Applications - NOLTA’95, NTA Research Society of IEICE, Las Vegas, 1995, pp. 555-558. [174] S. Amari, A. Cichocki, H.H. Yang: Recurrent neural networks for blind separation of sources, Int. Symposium on Nonlinear Theory and its Applications - NOLTA’95, NTA Research Society of IEICE, Las Vegas, Dec. 1995, pp. 37-42. [175] A. Cichocki, W. Kasprzak, S. Amari: Multi-layer neural networks with a local adaptive learning rule for blind separation of source signals, Int. Symposium on Nonlinear Theory and its Applications - NOLTA’95, NTA Research Society of IEICE, Las Vegas, Dec. 1995, pp. 61-65. Patent Applications [1] A. Cichocki, R Zdunek, S. Amari, G. Hori, K. Umeno: ”Blind Signal Processing Method and System Using Modular and Hierarchical–Multilayer Processing for Blind Multidimensional Decomposition, Identification, Separation or Extraction of Hidden (Latent) Components (such as images, patterns, features, signals); especially, in applications to NMF (Non-negative Matrix Factorization), SCA (Sparse Component Analysis), and MCA (Morphological Component Analysis).”, Japanese patent application No. : 2006-225978, March 2006.

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[2] T. Hoya and A. Cichocki, ”Noise reduction by cascaded singular value decomposition filtering”, Patent Application No. 2002-129820, Japan, May. 2002. [3] G. Hori, S. Amari, A. Cichocki, Y. Mizuno, Y. K. Aihara: ”EEG signal processing method for judgment of brain death using independent component analysis”, Japanese patent application No. : 2000-225978 [4] T. Hoya, A. Cichocki, T. Murakami, and Y. Ishida, ”Noise reduction by combined signal preprocessing and adaptive filtering techniques”, Patent Application No. 2002-129752, Japan, May. 2002. [5] T. Hoya, A. K. Barros, T. Rutkowski, and A. Cichocki, “A signal extraction system”, Patent Application No. 2002-289797, Japan, Oct. 2002. [6] T. Hoya, T. Murakami, A. Cichocki, and Y. Ishida, “Noise reduction by a combined signal preprocessing and adaptive filtering Techniques”, Patent Application, U.S.A. 10/426,624, May. 2003. Developed software and toolboxes available free to scientific community A. Cichocki, S. Amari, K. Siwek A.H Phan et al., ICALAB Toolboxes, (ICA- Independent Component Analysis http://www.bsp.brain.riken.go.jp/ICALAB http://www.bsp.brain.riken.go.jp/ICALAB/ICALABImageProc/ A. Cichocki and R. Zdunek NTFLAB (NTF-Nonnegative Tensor Factorization) http://www.bsp.brain.riken.jp/ICALAB/NTFLABSignalProcDownload.php A. Cichocki and R. Zdunek NMFLAB (NMF- Nonnegative Matrix Factorizations) Toolboxes for Signal Processing and Image Processing http://www.bsp.brain.riken.jp/ICALAB/nmflab.html Selected scientific contributions with the high citation index according to the Google Scholar:

1. Cichocki A. and Amari S. Adaptive Blind Signal and Image Processing, -Monograph, John Wiley, 2003, Chichester, UK,

2. Amari S., Cichocki A., and Yang H.H.: "A new learning algorithm for blind signal separation," in Advances in Neural Information Processing Systems 1995, vol.8, (Cambridge, MA), pp.757-763, MIT Press, 1996.

3. Cichocki A. and Unbehauen R.: Neural Networks for Optimization and Signal Processing -- Monograph, 1993 - John Wiley & Sons and Tuebner Verlag Germany and USA NY.

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4. A. Cichocki, R. Zdunek, A.-H. Phan, and S. Amari: Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-way Data Analysis, John Wiley, ISBN: 978-0-470-74666-0, (552 pages), November 2009.

5. Amari S. and Cichocki A.: “Adaptive blind signal processing-neural network approaches” – (invited paper), Proceedings of the IEEE, vol.86, no.10, pp. 2026-2048, Oct. 1998.

6. S. Amari, T. Chen, and A. Cichocki, "Stability analysis of learning algorithms for blind source separation," Neural Networks, vol. 10, no. 8, pp. 1345-1351, 1997.

6. Cichocki A. and Unbehauen R. “Robust neural networks with on-line learning for blind identification and blind separation of sources”, IEEE Transaction on Circuits and Systems: Fundamental Theory and Applications, vol.43, pp. 894-906, 1996

8. Y. Li, A Cichocki, S Amari “Analysis of sparse representation and blind source separation”, Neural Computation, Vol. 16, No. 6, pp. 1193-1234, June 2004, MIT Press

9. A. Cichocki, R Unbehauen: "Robust learning algorithm for blind separation of signals" , Electronics letters, 1994

10. A Cichocki, R Zdunek, S Amari: Csiszar's divergences for non-negative matrix factorization: Family of new algorithms, 2006 – Springer,

Dr Cichocki has been invited to the Council of Canadian Academies Survey of Science and Technology Strengths as an author of one of the top 1% most highly cited papers in his field worldwide.

His profile is available at Google Scholar https://scholar.google.com/citations?user=wpZDx1cAAAAJ&hl=pl&oi=ao

http://www.harzing.com/pop_wine.htm#zip

Cichocki Andrzej h-index = 83 (i10-index 400). Total number of citations 36,000.